Coin overview
J
In progress1.18-20.8%
Last price (USDT)
97.23K
24h total (USDT)
213.54K
Total vol (USDT)
Ends in
2025-01-15 15:00:00 ~ 2025-01-22 09:30:00
Trading time (UTC+0)
2025-01-22 11:00:00 ~ 2025-01-22 23:00:00
Delivery time (UTC+0)
Total supply1.00B
Resources
Introduction
Jambo is building a global on-chain mobile network, powered by the JamboPhone — a crypto-native mobile device starting at just $99. Jambo has onboarded millions on-chain, particularly in emerging markets, through earn opportunities, its dApp store, a multi-chain wallet, and more. Jambo’s hardware network, with 700,000+ mobile nodes across 120+ countries, enables the platform to launch new products that achieve instant decentralization and network effects. With this distributed hardware infrastructure, the next phase of Jambo encompasses next-generation DePIN use cases, including satellite connectivity, P2P networking, and more. At the heart of the Jambo economy is the Jambo Token ($J), a utility token that powers rewards, discounts, and payouts.
Jambo (J) Satellite Launch Sale on Bitget LaunchX
Bitget is pleased to announce the listing of Jambo (J) on LaunchX. Bitget LaunchX is our innovative token distribution platform designed for the Web3 community. It enables users to discover promising projects early and gain access to project tokens during their initial stages. Go to LaunchX Project overview Jambo is building a global on-chain mobile network, powered by the JamboPhone—a crypto-native mobile device starting at just $99. Jambo has onboarded millions of users, particularly in emerging markets, through earn opportunities, DApp store, a multi-chain wallet, and more. Jambo's hardware network, with over 700,000 mobile nodes across more than 120 countries and regions, enables the platform to launch new products that achieve instant decentralization and network effects. With this distributed hardware infrastructure, the next phase of Jambo encompasses next-generation DePIN use cases, including satellite connectivity, P2P networking, and more. At the heart of the Jambo economy is the Jambo Token ($J), a utility token that powers rewards, discounts, and payouts. LaunchX details: • Coin name: Jambo (J) • Total supply: 1,000,000,000 J • LaunchX volume: 10,000,000 J (1% of total supply) • Fundraising target: $5,000,000 • Subscription price: 1 J = $0.5 • Committed coin: BGB • Exchange rate of BGB to J: to be announced. (Bitget will take consecutive snapshots of the spot price of BGB from January 17, 4:00 PM, to January 22, 10:00 AM (UTC+8). The average value of the BGB price during this period will be used as the snapshot price to calculate the exchange rate of BGB to J. Details will be announced after the subscription period ends.) • Individual max commit: 2000 BGB • Individual min commit: 20 BGB • Subscription hard cap: 20,000 J How does LaunchX work? 1. LaunchX adopts a commitment–subscription model. The more you commit, the more you can subscribe! 2. Bitget LaunchX participants can calculate their allocation using the following formula: allocation = (individual commitment ÷ total committed amount of all users) × total sale amount in the current LaunchX promotion. Note: If the committed token is other than USDT, the system will take consecutive snapshots of the spot price of the committed coin according to the set snapshot time. The average value of the price during the snapshot period will be used as the snapshot price. 3. Individual commitment cannot exceed the individual max commitment, and individual allocation cannot exceed the subscription hard cap. LaunchX timelines: Phase Date and time Subscription phase January 20, 10:00 AM – January 22, 10:00 AM (UTC+8) J allocation phase January 22, 10:00 AM – January 22, 6:00 PM (UTC+8) J/USDT spot trading launch time January 22, 6:00 PM (UTC+8) Reference: Bitget LaunchX: A tailor-made early token distribution for users and projects Links: Website: https://www.jambo.technology/ X: https://twitter.com/JamboTechnology Telegram: https://t.me/jambotechnology Terms and conditions 1. Users must complete identity verification to participate in the promotion. 2. All participants must strictly comply with Bitget's terms and conditions. 3. Sub-accounts, institutional accounts, and market maker accounts are not eligible for the promotion. 4. Bitget reserves the right to disqualify any user from participating in the promotion and confiscate their incentives if any fraudulent conduct, illegal activities (e.g., using multiple accounts to claim incentives), or other violations are found. 5. Bitget reserves the right to amend, revise, or cancel this promotion at any time without prior notice, at its sole discretion. 6. Bitget reserves the right of final interpretation of the promotion. Contact customer service if you have any questions. Disclaimer Cryptocurrencies are subject to high market risk and volatility despite high growth potential. Users are strongly advised to do their research as they invest at their own risk. Thank you for supporting Bitget! Join Bitget, the World's Leading Crypto Exchange and Web 3 Company Sign up on Budget Now >>> Follow us on Twitter >>> Join our Community >>>
Tokyo politician to develop AI tool to manage political funds and aggregate public opinion
A young Sci-Fi writer politician in Tokyo wants to govern the nation with AI, and has announced he will create a tool to aggregate public opinion, manage political funds, and even shape policy. Takahiro Anno’s vision for “Digital Democracy 2030” is not favored by everyone, however, and falls in line with previous disturbing ideas put forth by the J-gov about leaning into AI rulership. 2024 Tokyo gubernatorial hopeful and self-proclaimed Sci-Fi writer Takahiro Anno thinks AI could help clean up governance in Japan. According to local media , the software engineer (who came in fifth in the 2024 Tokyo election) has announced he will create an open-source tool for aggregating public opinion, managing funds, and shaping policy. Anno’s controversial vision of ‘Digital Democracy 2030’ Anno explained on January 16 during a speech in Shinjuku Ward, Tokyo, that his vision for “ Digital Democracy 2030 ” sees artificial intelligence taking a central role in shaping politics, with Nikkei reporting that the tool aims to “manage political funds” and “aggregate public opinion.” Further, it will connect its findings to policy creation. Source: X On the surface this may seem like a one-off, pie-in-the-sky idea from another random software engineer and science-fiction geek, but Anno actually has big state ties as a current advisor to GovTech Tokyo, an organization dedicated to digital transformation (DX) which is 100% bankrolled by the Tokyo Metropolitan Government. See also TV channel removes interview about woman who sent $855K to scammers in Brad Pitt AI romance scam Further, back in November of last year, Japan’s Digital Administrative and Financial Reform Council released a document describing how artificial intelligence, drones, and robots can be used in the implementation of a new kind of surveillance state to better govern the nation — ideas right in line with Anno’s proclamations. Japanese reactions mixed, residents still struggling with immediate fiscal hardships Social media responses to the Nikkei article on Anno were mixed, as residents of Japan seem to think there are much more important matters to attend to. One user even questioned (translated by Google): “Is there any point in using AI as an intermediary? Another public money business?” Still, other commenters said the idea was “amazing” and expressed interest in getting the AI tool in place. As Cryptopolitan has previously reported , Japan’s current economic struggles are increasing for everyday individuals, with a flagging JPY, skyrocketing food prices, and a growing elderly population that cannot afford to retire on the state’s poverty-line pensions. As such, it’s really no wonder people are skeptical of a well-funded, 34-year-old Sci-Fi writer’s ideas for how their money should be spent. A Step-By-Step System To Launching Your Web3 Career and Landing High-Paying Crypto Jobs in 90 Days.
Bitget Partners With Jambo to Fund Telecom Satellite Launch
Bitget is partnering with Jambo, a blockchain-native mobile network, to raise funds for a satellite launch. Jambo hopes to raise $5 million through a token sale and fund its satellite launch to expand access to decentralized services. This news comes from an exclusive press release shared with BeInCrypto. Bitget and Jambo Aim for the Stars Bitget, one of the world’s leading crypto exchanges, has set quite an ambitious goal with this Jambo collaboration. Jambo, which launched in 2022 to become “the WeChat of Africa,” released a blockchain-based phone last year through a partnership with Aptos. Bitget CEO Gracy Chen described how her company could help the firm build satellite infrastructure: “Jambo’s vision of connecting the world through blockchain and mobile innovation aligns perfectly with our plan to support transformative projects. By facilitating Jambo’s satellite program through LaunchX, we aim to empower their efforts in bridging the digital divide and unlocking the potential of Web3 for emerging markets,” Chen claimed. Through this partnership, Jambo can fulfill several of its core goals at once. Its native token, ‘J,’ is at the heart of Jambo’s DeFi ecosystem, and the firm will launch this token through Bitget’s LaunchX platform. CEO James Zhang stressed that the satellite launch will vertically integrate Jambo’s communication hardware, creating new possibilities in the underlying ecosystem. Bitget can also gain a great deal of notoriety from the Jambo satellite launch. Although its BGB token reached an all-time high in late December, it saw significant corrections afterward. Bitget took the drastic step of burning 800 million tokens to stabilize and boost BGB’s value, but it has stagnated since. A highly publicized launch like this could attract a lot of goodwill. Furthermore, the exchange reportedly plans to expand across several global markets and is considering Lithuania as a regional hub for MiCA compliance in the EU. These efforts could continue to drive BGB’s demand in the long term. Bitget Token (BGB) Monthly Price Performance. Source: BeInCrypto Ultimately, the goal of launching a satellite may still be challenging. Jambo plans to aim for $5 million in fundraising through Bitget LaunchX, but that is probably not enough to launch a satellite alone. Prices vary greatly, but even the cheapest options typically cost above $10 million. Although details about these challenges are yet to be addressed by Jambo, the firm might be looking into additional funding opportunities to achieve the project outcome.
Bitget LaunchX to Support Jambo’s $5 Million Fundraising for Satellite Launch Program
Victoria, Seychelles, January 17, 2025 – Bitget , the leading cryptocurrency exchange and Web3 company, is proud to announce the upcoming LaunchX event for Jambo, the world’s largest on-chain mobile network. Jambo aims to raise $5 million through a token sale on Bitget LaunchX to fund its ambitious satellite launch program, an initiative designed to connect a global network of JamboPhones and expand access to decentralized services. Jambo is a global leader in the blockchain ecosystem through its $99 crypto-native smartphone, the JamboPhone. With over 700,000 units sold in 2024 alone, the company is at the forefront of bringing Web3 technologies to emerging markets. The satellite program is the next phase to vertically integrate borderless data access to JamboPhone users around the world. The JamboPhone is an affordable, high-spec device pre-installed with Web3 applications, enabling users to engage in decentralized finance, gaming, and earning opportunities. With its satellite program, Jambo is taking its ecosystem to the next level by securing uninterrupted user data access, even in remote areas with limited internet connectivity. LaunchX is Bitget’s premier token launch platform, enabling users to access early-stage crypto projects with strong fundamentals and innovative goals. By participating in LaunchX, users not only gain access to promising tokens but also contribute to the advancement of revolutionary technologies. Gracy Chen, CEO of Bitget, remarked: “Jambo’s vision of connecting the world through blockchain and mobile innovation aligns perfectly with our plan to support transformative projects. By facilitating Jambo’s satellite program through LaunchX, we aim to empower their efforts in bridging the digital divide and unlocking the potential of Web3 for emerging markets. This is a testament to Bitget’s commitment to enabling projects that drive long-term value for the global crypto ecosystem.” Jambo’s satellite launch initiative represents a bold move to integrate its connectivity infrastructure vertically. The program seeks to provide reliable internet access to over 3 billion people who currently lack connectivity, empower crypto adoption through consistent data access, and future-proof its network for the growing demands of the decentralized world. “By owning our connectivity infrastructure, we can ensure that our users always stay connected to the decentralized economy,” said James Zhang, CEO of Jambo. “The satellite program not only strengthens the JamboPhone’s competitive edge but also creates new possibilities for blockchain-based mobile applications, from decentralized validators to peer-to-peer networking.” Jambo ($J) is the second project featured on Bitget LaunchX, following the successful launch of Fuel Network ($FUEL), which raised its target of $5.5 million with overwhelming interest, receiving a total commitment of over 400 million USDT from 141,430 participants. The Jambo ($J) token lies at the heart of Jambo’s ecosystem, offering rewards, discounts, and payouts that fuel the decentralized economy envisioned by the company. Through Bitget LaunchX, users can join this pioneering initiative and be part of a journey that merges blockchain, hardware, and connectivity. This post is commissioned by Bitget and does not serve as a testimonial or endorsement by The Block. This post is for informational purposes only and should not be relied upon as a basis for investment, tax, legal or other advice. You should conduct your own research and consult independent counsel and advisors on the matters discussed within this post. Past performance of any asset is not indicative of future results.
Jambo (J): Transforming Africa’s Digital Economy Through Web3 and Decentralized Finance
What is Jambo (J)? Jambo (J) is an on-chain mobile network project designed to revolutionize decentralized finance and introduce millions of Africans to Web3 technology. It prioritizes scalability, security, and user accessibility. It simplifies how people access digital financial tools while fostering creativity and community. Who Created Jambo (J)? Jambo was founded in 2021 by siblings James Zhang and Alice Zhang. Born and raised in the Democratic Republic of Congo, the pair grew up with a firsthand understanding of Africa’s untapped potential and its challenges. Their family has invested in Africa’s economic growth for generations, which inspired their mission to create something impactful for the continent. James Zhang, a graduate of New York University with a degree in computer science, has a strong background in technology and blockchain. Alongside his sister Alice, he envisioned Jambo as a way to onboard the next million—or potentially billion—Africans to Web3. The Zhang siblings are blockchain enthusiasts who believe in the transformative power of decentralized technologies to create financial prosperity and equality. What VCs Back Jambo (J)? Jambo’s ambitious vision has attracted significant support from some of the world’s most prominent venture capitalists. Major investors in Jambo include Paradigm, ParaFi Capital, Pantera Capital, Delphi Ventures, Kingsway Capital, Gemini Frontier Fund, BH Digital, Graticule Asset Management Asia, Shima Capital, Morningstar Ventures, Coinbase Ventures, Tiger Global, and more. How Jambo (J) Works Jambo is a comprehensive ecosystem designed to empower individuals through technology, education, and financial tools. Here’s how it operates: 1. The Jambo SuperApp At the heart of Jambo’s ecosystem is the Jambo SuperApp, a multi-functional digital platform that brings earning opportunities, education, and financial services together. The app is tailored to meet the needs of Africa’s diverse population, offering features such as: ● Play-to-Earn Games: Users can participate in fun games and get incentives. ● NFT Marketplace: The app allows users to buy, sell, and trade non-fungible tokens (NFTs), opening new opportunities for artists and creators. ● Crypto Trading: Jambo simplifies cryptocurrency trading, making it accessible to newcomers and experienced users alike. ● Education: The platform provides Web3 and blockchain education to help users understand and leverage decentralized technologies. Through personalized recommendations, the SuperApp ensures that users engage with content and opportunities that match their interests and goals. This creates a unique and rewarding experience for everyone. 2. Jambo Phone In addition to the SuperApp, Jambo is making strides in hardware innovation. The company launched the Jambo phone, an affordable device tailored for Africa’s mobile-first population. This product bridges the technology gap by giving people access to blockchain-based tools and DeFi applications in a user-friendly way. 3. On-the-Ground Education and Community Building Jambo’s success is built on its grassroots approach to education and community engagement. The company has established local offices across Africa and partnered with thousands of internet cafes and college booths to provide access to high-speed internet and educational programs. These initiatives empower users to learn about Web3 technology in a way that is tailored to their local communities. Jambo has also built a network of ambassadors who help spread the word and educate others about blockchain technology. By the end of 2022, Jambo aimed to expand into more than 15 cities and reach over 200,000 active community members, students, and ambassadors. This approach ensures that the adoption of Web3 is organic and culturally relevant. 4. Simplified Economy and Earning Opportunities One of Jambo’s standout features is its simplified economy, which consolidates all earning opportunities within the SuperApp. Users can manage their earnings, track their progress, and withdraw funds seamlessly. Whether they’re earning through play-to-earn games, trading crypto, or selling NFTs, the app ensures that every activity is straightforward and user-friendly. 5. Security and Privacy Jambo prioritizes user security and privacy. The platform incorporates state-of-the-art security measures to protect user data and earnings. This commitment to safety ensures that users can explore and thrive in the Web3 ecosystem without concerns about their information or assets being compromised. 6. The Jambo Token (J) Launching in January 2025, the Jambo token (J) will serve as the backbone of the Jambo ecosystem. It will enable users to participate in decentralized finance activities, access exclusive benefits, and receive incentives for their engagement on the platform. The introduction of the J token marks a significant step forward in creating a fully integrated and self-sustaining digital economy for Africa. J Goes Live on Bitget Jambo’s mission goes beyond technology; it’s about empowering individuals and transforming lives. With visionary founders, strong investor support, and a user-first approach, Jambo is set to redefine what’s possible in the world of Web3 and decentralized finance. By simplifying access to blockchain technology and fostering economic inclusion, Jambo is unlocking the potential of a continent and empowering its people to thrive in the digital age. Trade J on Bitget now! J on Bitget Pre-Market J is a part of Bitget Pre-Market, a platform where users can trade tokens over-the-counter before the token is listed for spot trading. Start time: 15 January, 2025 Bitget Pre-Market offers flexibility in trading activities with two settlement options: ● Coin settlement, which uses a 'cash on delivery' method where a security deposit is forfeited if the seller fails to deliver. ● USDT settlement, a new option where trades are settled in USDT at the average index price at the last minute. To use Bitget Pre-Market, follow these simple steps: ● Step 1: Go to the Bitget Pre-Market page. ● Step 2: ○ For Makers: ■ Choose the desired token and click on ‘Post Order’. ■ Specify Buy or Sell, enter price and quantity, review details, then confirm. ○ For Takers: ■ Choose the desired token, pick ‘Sell’ or ‘Buy’, select the pending order, enter quantity, and confirm. Get J on Bitget Pre-Market now! Jambo (J) on Bitget LaunchX Bitget is pleased to announce the listing of Jambo (J) on LaunchX. Jambo (J)’s LaunchX details: • Total supply: 1,000,000,000 J • LaunchX volume: 10,000,000 J (1% of total supply) • Fundraising target: $5,000,000 • Subscription price: 1 J = $0.5 • Committed coin: BGB • Exchange rate of BGB to J: to be announced. Timelines: • Subscription phase: January 20, 10:00 AM – January 22, 10:00 AM (UTC+8) • Allocation phase: January 22, 10:00 AM – January 22, 6:00 PM (UTC+8) Join LaunchX now! How to Trade J on Bitget Spot Listing time: January 22, 2025 Step 1: Go to JUSDT spot trading page Step 2: Enter the amount and the type of order, then click Buy/Sell Trade J on Bitget now! Disclaimer: The opinions expressed in this article are for informational purposes only. This article does not constitute an endorsement of any of the products and services discussed or investment, financial, or trading advice. Qualified professionals should be consulted prior to making financial decisions.
QMDB: Quick Merkle Database
License: arXiv.org perpetual non-exclusive license arXiv:2501.05262v2 [cs.NI] 14 Jan 2025 by Isaac Zhang Ryan Zarick Daniel Wong Thomas Kim Bryan Pellegrino Mignon Li Kelvin Wong LayerZero Labs Abstract Quick Merkle Database (QMDB) addresses longstanding bottlenecks in blockchain state management by integrating key-value (KV) and Merkle tree storage into a single unified architecture. QMDB delivers a significant throughput improvement over existing architectures, achieving up to 6× over the widely used RocksDB and 8× over NOMT, a leading verifiable database. Its novel append-only twig-based design enables one SSD read per state access, O(1) IOs for updates, and in-memory Merkleization on a memory footprint as small as 2.3 bytes per entry enabling it to run on even modest consumer-grade PCs. QMDB scales seamlessly across both commodity and enterprise hardware, achieving up to 2.28 million state updates per second. This performance enables support for 1 million token transfers per second (TPS), marking QMDB as the first solution achieving such a milestone. QMDB has been benchmarked with workloads exceeding 15 billion entries (10× Ethereum’s 2024 state) and has proven the capacity to scale to 280 billion entries on a single server. Furthermore, QMDB introduces historical proofs, unlocking the ability to query its blockchain’s historical state at the latest block. QMDB not only meets the demands of current blockchains but also provides a robust foundation for building scalable, efficient, and verifiable decentralized applications across diverse use cases. †† 1Introduction Updating, managing, and proving world state are key bottlenecks facing the execution layer in modern blockchains. Within the execution layer, the storage layer, in particular, has traditionally traded off performance (throughput) and decentralization (capital and infrastructure barriers to participation). Blockchains typically implement state management using an Authenticated Data Structure (ADS) such as a Merkle Patricia Trie (MPT). Unfortunately, typical MPT-based ADSes incur a high amount of write amplification (WA) with many costly random writes for each state update, which requires storing the entire structure in DRAM to avoid getting bottlenecked by the SSD. As a result, the performance and scaling of blockchains is I/O-bound, and the key to unlocking higher performance with larger datasets is to optimize the use of SSD IOPS more efficiently and reduce WA. We present Quick Merkle Database (QMDB), a resource-efficient SSD-optimized ADS with in-memory Merkleization that implements a superset of the app-level features of existing RocksDB-backed MPT ADSes with 6× throughput on large datasets. Qmdb performs state reads with a single SSD read, state updates with O(1) IO, and performs Merkleization fully in-memory with no SSD reads or writes. These operations are theoretically optimal regarding disk IO complexity. Additionally, QMDB has a DRAM footprint small enough to run on consumer-grade PCs. Blockchain state storage is typically handled by an Authenticated Data Structure (ADS) which acts as a proof layer (e.g. Merkle Patricia Trie (MPT)) in combination with a physical storage layer. The proof layer efficiently generates inclusion and exclusion proofs against the world state, while the physical storage layer stores the actual world state keys and values. In many existing blockchains, these layers are each stored in a separate general-purpose key-value store such as RocksDB, resulting in duplicated data and general inefficiency. Storing a MPT (O(logN) insertion) in a general-purpose key-value store (O(logN) insertion) results in each state update incurring O((logN)2) SSD IOs. QMDB eliminates this inefficiency by unifying the world state and Merkle tree storage, persisting all state updates in an append-only log, and eliminating all SSD reads and writes from Merkleization. By grouping updates into fixed-size immutable subtrees called twigs, QMDB can Merkleize state updates without reading or writing any world state; this essentially compresses the Merkle tree by several orders of magnitude, allowing it to be stored in a modest amount of DRAM. QMDB leverages typical blockchain workload characteristics to eliminate features commonly found in KVDBs—such as key iterations—thereby reducing performance bottlenecks. These optimizations enable QMDB to achieve 6× throughput compared to RocksDB, a general-purpose key-value database that does not perform Merkleization. We also show that QMDB outperforms a prerelease version of NOMT, a state-of-the-art verifiable database, by up to 8×. We validate QMDB’s scaling characteristics with experiments up to 15 billion entries (10X of Ethereum’s 2024 state size) and show it scales on both consumer-grade and enterprise-grade hardware. QMDB is a transformative improvement for blockchain developers, addressing today’s storage challenges and unlocking new possibilities for blockchain applications. In particular: 1) QMDB can serve massive workloads with the same amount of DRAM, allowing blockchains to handle more users and transactions; 2) Based on its low memory overhead per entry, QMDB can theoretically scale up to 280 billion entries on a single server, far exceeding any blockchain’s requirements today; and 3) QMDB can scale down to consumer-grade hardware, decreasing barriers to participation and improving decentralization. Figure 1:Entries are inserted sequentially into the leaves of the Fresh twig, and all leaves have the same depth. The twig eventually transitions into the Full state. As Entries are deleted, Full twigs become Inactive, then transition to Pruned. Upper nodes are recursively pruned after both of their children are pruned. 2Background We explain the design of other verifiable databases and related data structures, including prior work reducing write amplification of verifiable databases [ 19 , 13 ]. MPTs combine the efficient proof generation of the Merkle tree with the fast lookups of the Patricia trie and are a common choice for ADS on today’s blockchains [ 23 ]. In a database of N items, updating a single state entry in an MPT has a time complexity of O(log(N)) [ 17 ]. However, MPT and other existing trie-based ADSes suffer from large proofs and a dependency on the client having a large amount of physical memory to avoid excessive random SSD reads. At the same time, MPTs are not suitable for storage on flash storage, as the randomly distributed update-heavy workload results in high WA. To top it off, the worst-case size for inclusion and exclusion proofs can be quite large. These factors result in Merkleization becoming a significant bottleneck that limits the overall throughput of the execution layer and the blockchain. AVL tree based ADSes are popular alternatives to MPTs, as they achieve faster updates, lookups, and proof generation due to the self-balancing AVL tree. The AVL tree is path-dependent, unlike the MPT, meaning its state root is influenced by the specific sequence of state change actions. AVL trees provide a marginal performance increase over MPTs in the average case, but still suffer from O(log N) tree nodes modifications per state update. LVMT [ 13 ] proposes a layered storage model to reduce the space and complexity of maintaining authenticated blockchain states. By partitioning the state into multiple segments and using cryptographic accumulators, it compresses less frequently accessed data while preserving verifiability. Proof generation becomes simpler, as intermediate accumulators shorten authentication paths. However, integrating multiple layers increases system complexity and demands careful configuration—suboptimal settings can lead to poor performance. Furthermore, LVMT depends on well-optimized cryptographic primitives. MoltDB [ 14 ] improves on existing two-layer MPT designs by segregating states by recency and coupling that with a compaction process. It reduces I/O and shows increased throughput of 30% over Geth. NOMT is a state-of-the-art ADS that uses a flash-optimized layout for a binary Merkle tree with compressed metadata, overcoming some limitations of existing MPT-based ADS implementations. NOMT implements an array of improvements including tree arity, flash native layout, a write-ahead log, and caching. This design results in better performance than existing solutions and has garnered interest in the space. However, NOMT remains an implementation-level optimization of MPT, offering only constant-factor reductions in disk I/O. It still faces inherent asymptotic limitations and write amplification issues. Additionally, it is affected by the key sparsity problem commonly observed in trie-based structures. Merkle Mountain Range (MMR) [ 22 ] enable compact inclusion proofs and are append-only, which makes the IO pattern for updating state conducive to efficient usage of SSD IOPS. Each MMR is a list of Merkle subtrees (peaks), and peaks of equal size are merged as new records are appended. MMRs are not suitable for live state management, as they cannot natively handle deletes, updates, lookups by key, and exclusion proof generation. As a result, MMRs have generally found success in their use for historical data management [ 18 ] where the key is just an index. Acceleration of Merkle tree computation has been an area of active research, with several proposed techniques such as caching [ 8 , 5 ], optimizing subtrees [ 4 ], and using specialized hardware [ 12 , 6 ]. These improvements are orthogonal to QMDB and could be applied to QMDB to further improve its performance and efficiency. Verifiable ledger databases are systems that allow users to verify that a log is indeed append-only, of which blockchains are a subset. A common approach to implementing a verifiable ledger database is deferred verification [ 25 , 24 , 3 ]. GlassDB [ 25 ] uses a POS-tree (a Merkle tree variant) as an ADS for efficient proofs. Amazon’s QLDB [ 2 ], Azure’s SQLLedger [ 3 ], and Alibaba’s LedgerDB [ 24 ] are commercially available verifiable databases that use Merkle trees (or variants) internally to provide transparency logs. VeritasDB [ 21 ] uses trusted hardware (SGX) to aid verification. The key difference between these databases and QMDB is that QMDB is optimized for frequent state updates and real-time verification of the current state (as opposed to verification of historical logs and deferred verification). Field Description Purpose Id Unique identifier (e.g., nonce) Prove key inclusion Key Application key Identify the key Value Current state value the key Serve application logic NextKey Lexicographic successor of Key Prove key exclusion OldId Id of the Entry previously containing Key Prove historical inclusion / exclusion OldNextKeyId Id of the Entry previously containing NextKey Prove key deletion Version Block height and transaction index Query state by block height Table 1:Fields in a QMDB entry.ID and Version are 8 bytes. Key has up to28bytes and Value can hold up to224bytes. 3QMDB Design QMDB is architected as a binary Merkle tree illustrated in Figure 1 . At the top is a single global root that connects a set of shard roots, each of which represents the subtree of the world state that is managed by an independent QMDB shard. The shard root itself is connected to a set of upper nodes, which, in turn, are connected to fixed-size subtrees called twigs; each of these twigs has a root that stores the Merkle hash of the subtree and a bitmap called ActiveBits to track which entries are part of the most current world state. The twig root is determined by the sequence of entries, making it path-dependent. Entries (the twig’s leaves) are append-only and immutable, making it unnecessary to read or write the entry root during Merkleization; this results in QMDB only ever reading/writing the global root, shard roots, upper nodes, and twig roots during Merkleization. The twig essentially compresses the actual state keys and values into a single hash and bitmap, making the data required for Merkleization small enough to fit in a small amount of DRAM rather than being stored on SSD. In this section we begin by explaining the underlying storage primitives used to organize state data (Section 3.1 ), followed by a discussion of the indexer in Section 3.2 . In Section 3.3 we describe the high-level CRUD interface exported by QMDB to clients. In Section 3.4 we describe how the storage backend and indexer facilitate generation of state proofs, and discuss how these state proofs can be statelessly validated. Finally, in Section 3.5 we explain how QMDB takes advantage of additional optimizations such as sharding and pipelining to scale throughput via improved parallelism. 3.1Entries and Twigs The entry (Table 1 ) is the primitive data structure in QMDB, encapsulating key-value pairs with the metadata required for efficient proof generation. Entries can be extended to support features such as historical state proof generation (Section 3.4 ). QMDB keys entries by the hash of the application-level key, resulting in improved load balancing via uniform key distribution across shards (Section 3.5 ) State Description Entries Twig Root Fresh Entries ≤2047 DRAM DRAM Full 2048 Entries SSD DRAM Inactive 0 active Entries Deleted SSD Pruned Subtree deleted Deleted Deleted Table 2:As twigs progress through their lifecycle, their footprint in DRAM gets smaller. An inactive twig has 99.9% smaller memory footprint than a full twig. Twigs are subtrees within QMDB’s Merkle Tree; each twig has a fixed depth, by extension a fixed number of entries stored in the leaf nodes of the same depth (2048 in our implementation). A set of upper nodes connects all twigs to a single shard root, with null nodes to represent uninitialized values; these upper nodes are immutable once all their descendant entries have been initialized. In addition to the actual Merkle subtree, Twigs also store the Merkle hash of their root node and ActiveBits, a bitmap that describes whether each contained entry contains state that has not been overwritten or deleted. The twig essentially compresses the information required to Merkleize 2048 entries and their upper nodes (≥256kb) into a single 32-byte hash and a 256-byte bitmap (99.9% compression). This compression is the key to enabling fully in-memory Merkleization in QMDB. Fresh twigs reside completely in DRAM, and entries are sequentially inserted into its leaf nodes. Once a twig reaches 2048 entries, its contents are asynchronously flushed to SSD in a large sequential write and deleted from DRAM, maximizing SSD utilization and minimizing DRAM footprint. Each twig follows a lifecycle of 4 states: Fresh, Full, Inactive, and Pruned (Table 2 ). An example of the layout of QMDB’s state tree is presented in Figure 1 There is exactly one fresh twig per shard, and entries are always appended to the fresh twig. After all entries in the twig are marked inactive as a result of update and delete operations, the twig transitions into the inactive state before eventually being pruned and replaced by the Merkle hash of the root. Upper nodes that contain only pruned twigs are recursively pruned, further reducing the memory footprint of QMDB; a dedicated garbage collection thread duplicates old valid entries into the fresh twig, reducing fragmentation and allowing larger subtrees to be pruned. In theory, once the entire subtree originating at a child of the shard root is pruned, the root itself can be pruned to reduce the depth of the tree by one. The grouping of entries into twigs reduces the DRAM footprint of QMDB to the degree that all nodes affected by Merkleization can be stored in a small amount of DRAM. In a hypothetical scenario with 230 entries (approx. 1 billion), the system must keep at most 219 (2302048) 288-byte (32-byte twig root hash 2048-bit ActiveBits bitmap) full twigs, 1 fresh twig and 219−1 32-byte (node hash) upper nodes totaling around 160 megabytes. In practice, the majority of the 219 twigs will be pruned, resulting in the average size being much smaller. Inactive and Pruned twigs cannot be modified, and thus do not require further Merkleization. Fresh and Full twigs must be Merkleized every time the ActiveBits bitmap is changed, and Fresh twigs must additionally be Merkleized every time an entry is added. The upper nodes of the Merkle tree are recomputed on startup and are never persisted to SSD–this recomputation requires reading all twig hashes from SSD and performing 2 hashes per twig, and can be completed in a matter of milliseconds for the previous example of 1 billion entries. QMDB stores an entry every time state is modified, making the state tree grow proportionally to the number of state modifications. To combat this tree growth, a dedicated compaction worker periodically compacts QMDB’s state tree by removing and re-appending old entries to the fresh twig, accelerating the progression of the twig lifecycle and allowing more subtrees to be pruned. The compaction logic must be deterministic when used in a consensus system or for stateless validation. The current implementation ensures that the active entry ratio per shard remains above a predefined threshold, triggering compression during updates and insertions. QMDB’s Merkle proof size and proof generation complexity grow proportionally to log(U) of the number of state updates (U) rather than the number of unique keys (K) due to its append-only nature. However, the ratio of U to K remains small enough that the order-of-magnitude improvement in Merkleization performance dominates the small additional cost. Assuming 10,000 transactions per second and an average of 5 KV updates per transaction, the tree depth after one year will be at most 41 (log2(10000∗5∗3600∗24∗365)); however, in practice the actual depth will be much shallower due to pruning of overwritten subtrees and garbage collection. In addition, ZK-proofs can be used to compress the proof witness data which drastically reduces proof verification cost, avoiding end-to-end bottlenecks in the proof size. 3.2Indexer The indexer maps the application-level keys to their respective entries, enabling QMDB’s CRUD interface. To support efficient insertion and deletion of entries (Section 3.3 ), the indexer must support ordered key iteration. The indexer can be freely swapped for different implementations depending on specific application needs, but we expect that QMDB’s default in-memory indexer will meet the resource requirements of the majority of use cases. This modularity potentially enables optimizations to increase the performance or memory efficiency of the indexer such as those found in systems such as SILT [ 15 ] or MICA [ 16 ]. QMDB’s default indexer consumes approximately 15.4 bytes of DRAM per key and serves key lookups in-memory to minimize SSD I/Os. This efficiency is achieved by using only the 9 most significant bytes of each key, which slightly increases the likelihood of key collisions but strategically trades worst-case performance for reduced DRAM usage. Of these 9 bytes, the first 2 bytes serve as the sharding key for the indexer, leaving a 7-byte memory footprint for key storage. The remaining 8.4 bytes consist of a 6-byte SSD position offset and additional data structure overhead, which is amortized across all keys. Using just 16 gigabytes of DRAM, the in-memory indexer can index more than 1 billion entries, making it suitable for a wide range of applications. We chose the B-tree map as the basis for the underlying structure of QMDB’s default indexer to take advantage of B-tree’s high cache locality, low memory overhead, support for ordered key iteration, and graceful handling of key collisions. We use fine-grained reader-writer locks (determined by the first two bytes of the key hash) to minimize contention when updating entries. 3.3CRUD interface QMDB exposes a CRUD (Create, Read, Update, Delete) interface, and in this section we provide a high-level overview of how each operation is implemented. In all examples, we present the operation of the system when using the default in-memory indexer; other indexers may require more reads or writes to serve the same workload. For each operation, we present an intuitive explanation followed by a more formal description along with a description of the SSD I/O required to synchronously handle the request. All writes in QMDB are buffered in twigs (DRAM) and persisted to SSD in batches, so each SSD write is amortized across 2048 entries; to precisely express the cost of each operation, we refer to a entry write as 12048 of a single batched flush to SSD. For brevity, we omit the Id, Version, and Value fields when describing new entries (see Table 1 ), so an entry E is defined as: E=(Key,NextKey,OldId,OldNextKeyId) Read begins by querying the indexer for the file offset of the entry corresponding to a given key; this file offset is used to read the entry in a single SSD IO. Update first reads the most current entry for the updated key, then appends a new entry to the fresh twig. More formally, if E is the most current entry, the new entry E′ appended to the fresh twig derives its OldId and OldNextKeyId from E as follows: E′=(K,E.nextKey,E.Id,E.OldNextKeyId) Updating a key in QMDB incurs 1 SSD read and 1 entry write. Create intuitively involves appending one new entry and updating one existing entry; the existing entry whose Key and NextKey define a range that coincides with the created key must be updated with a new NextKey. This begins by first reading the entry Ep corresponding to the lexicographic predecessor (prevKey) to the created key K. Note that Ep must fulfill the condition Ep.Key EK=(K,Ep.nextKey,Ep.Id,En.Id) Ep′=(prevKey,K,Ep.Id,En.OldId) The ActiveBit of Ep is set to false (in memory), and the indexer is updated so that prevKey points to the file offset of Ep′ and K points to the file offset of EK. Creating a key in QMDB incurs 1 SSD read and 2 entry writes. Delete is implemented by first setting the activeBit to false for the most current entry corresponding to K, then updating the entry for prevKey. First, the entries EK and Ep corresponding to the keys K and prevKey are read from SSD, and the ActiveBits for the twig containing EK is updated. Next, a new entry for PrevKey is appended to the fresh twig: Ep′=(prevKey,EK.nextKey,Ep.Id,EK.OldNextKeyId) Deleting a key in QMDB incurs 2 SSD reads and 1 entry write. 3.4Proofs The remainder of this section describes how each field of the QMDB entry enables the generation of various state proofs. For illustrative purposes, we present proofs of the state corresponding to a key K and the most current Merkle root R, and denote fields of an entry E as E.fieldName. All proofs are Merkle proofs and as a result can be statelessly verified. Inclusion is proved by presenting the Merkle proof π for entry E such that E.Key=K; this entry E can be obtained after querying the corresponding file offset from the indexer. Exclusion is proved by presenting the inclusion proof of E such that E.Key Historical inclusion and exclusion at block height H can be proven for a key K by providing the inclusion proof of an entry such that K is represented by this entry at the given version (block height). QMDB uses OldId and OldNextKeyId to form a graph that enables the tracing of keys over time and space despite updates, deletions, and insertions. OldId links the current entry to the last inactive entry with the same key and OldNextKeyId links to the entry previously referenced by NextKey (when the entry for NextKey is deleted). When proving historical inclusion or exclusion, QMDB traverses the OldId pointer to move backwards in “time”, and the NextKey and OldNextKeyId pointers to move to different parts of the key space at a given block height. Reconstruction of historical state The graph structure defined by OldId and OldNextKeyId can also be used to reconstruct the Merkle tree and the world state at any block height. The Version field tracks the block height and the transaction index where the entry was created, allowing the precise reconstruction of historical states at specific block heights. 3.5Parallelization Figure 2:QMDB prefetches data (prefetcher), performs the state transition (updater), then commits the updated state to the Merkle tree and persistent storage (committer). State updates are parallelized in QMDB through sharding and pipelining. QMDB shards its key space into contiguous spans using the most significant bits—for example, the first 4 bits can create 16 shards—with boundary nodes to define logical boundaries that prevent state modifications from crossing shard boundaries (i.e., PrevKey and NextKey will always fall within the same shard). This sharding enables QMDB to better saturate underlying hardware resources and scale to bigger or multiple physical servers. In addition, QMDB implements a three-stage pipeline (Prefetch-Update-Flush) to allow the transaction processing layer to better saturate QMDB itself. For applications with relaxed synchronicity for state updates, QMDB is able to interleave computation across overlapping blocks. This cross-block and intrablock parallelism allows QMDB to more fully saturate available CPU cycles and SSD IOPS. Clients interact with QMDB by enqueueing key-value CRUD requests; updates are requested by writing the old Entry and new Value into the EntryCache directly, while deletions and insertions only require the key and new entry respectively. The pipeline is illustrated in Figure 2 , and is managed by three workers: the fetcher, the updater, and the committer. Each stage is shown in rectangles with solid lines, and the workers communicate via producer-consumer task queues in shared memory. The fetcher reads relevant entries from SSD into the EntryCache in DRAM when necessary (Deletion and Insertion), while the updater appends new entries and updates the indexer. Once the fetcher and updater finish processing a block, the committer asynchronously Merkleizes the updates and flushes the full twigs to persistent storage. The QMDB pipeline has N+1 serializability, which guarantees that state updates are visible in the next block. This is implemented by enforcing that the prefetcher cannot run for block N until the updater finishes processing block N−1. 4Evaluation In this section, we present a preliminary evaluation of the performance of QMDB and compare it to RocksDB and NOMT. On a comparable workload and evaluation setup, QMDB achieves 6× higher updates per second than RocksDB and 8× higher updates per second than NOMT. When measuring the performance of QMDB, we generate 100,000 transactions per block–each creating 10 entries–and run the workload for 7000 blocks to create a total of 7 billion entries. Periodically (every billion entries) we test the throughput and latency of reads, updates, deletions, and creations, and after all 7 billion entries are populated we measure transactions per second (TPS) using transactions consisting of 9 writes, 15 reads, 1 create, and 1 delete. 4.16X more updates/s than key-value DBs Figure 3 shows the throughput of QMDB compared to RocksDB (storing the application-level key-values with no Merkleization), demonstrating that QMDB delivers 6× more updates per second than RocksDB. This speedup is in fact an underestimate of QMDB’s advantage over RocksDB-based systems, given that all benchmarks compare QMDB with Merkleization to RocksDB without Merkleization. We believe the primary factor driving this speedup to be QMDB trading off functionality unnecessary for blockchain workloads for extra throughput. Examples of features and characteristics of RocksDB that are not required in blockchain workloads include efficient range/prefix queries and spatial locality of key-value pairs. We caveat that our RocksDB evaluation is preliminary and could be better optimized, as our results were gathered on an unsharded RocksDB instance with default parameters. We also tested RocksDB with the parameters recommended by the RocksDB wiki [ 9 ] with direct I/O enabled for reads and compaction, but did not observe noticeably better performance. We have also informally tested with MDBX but do not show those results here, as MDBX was significantly slower than RocksDB. Figure 3:QMDB shows a6×increase in throughput over RocksDB.QMDB is able to do 601K updates/sec with 6 billion entries and demonstrates superior performance across all operation types. These results were obtained on an AWS c7gd.metal instance with 2 SSDs and 64 vCPUs. 4.2Up to 8X throughput vs state-of-the-art For a more apples-to-apples comparison with a verifiable database that also performs Merkleization, we compared QMDB to NOMT [ 10 ]. NOMT performs Merkleization and stores Merkleized state directly on SSD, and can be directly compared to QMDB in terms of functionality. Both QMDB and NOMT aim to be drop-in replacements for general-purpose key-value stores like RocksDB, and aim to leverage the performance of NVMe SSDs. At the time of writing, both QMDB and NOMT are pre-release with significant optimizations in the pipeline for both systems, making a definitive comparison impossible at this point. We used the version of NOMT from November 2024. The steps we took to present a fair comparison include: evaluating QMDB and NOMT using their respective benchmark utilities, verifying the NOMT parameters with the authors [ 1 ], using the same hardware when evaluating each system, and normalizing the performance results against the workload. Unfortunately, we were unable to eliminate all variability, as NOMT does not support client-level pipelining and the evaluated version of QMDB did not support direct IO or io_uring (results for a newer version of QMDB with io_uring and direct IO are shown in § 4.3 ). Table 3 shows the results of our evaluation, demonstrating a 8× speedup in normalized updates per second (transaction count multiplied by state updates per transaction). NOMT’s default workload is a 2-read-2-write transaction, whereas QMDB is evaluated with a 9-write-15-read-1-create-1-delete transaction (based on our own analysis of the operation composition of historical Ethereum transactions; data available upon request). By normalizing the results based on the workload, we provide what we believe to be a fair representation of the comparative performance of these two systems. The read latency was comparable (30.7μs for QMDB and 55.9μs for NOMT) and close to the i3en.metal SSD read latency, which is in line with our expectations for both systems. We believe this performance gap to be primarily driven by SSD write amplification, given that NOMT buffers in-place updates in a write-ahead log whereas QMDB’s entries are immutable by design. This results in persistent storage writes for potentially every state update and Merkleization for NOMT, compared to QMDB where a SSD write is only required every 2048 updates and zero SSD accesses are required for Merkleization. We note that QMDB’s performance relies on its indexer, which incurs some DRAM overhead. Compared to NOMT’s overhead of 1–2 bytes per entry, QMDB incurs an additional 14 bytes per entry with its in-memory indexer and an additional 1–2 bytes per entry with its hybrid indexer). We consider this to be a reasonable trade-off given the 8× increase in throughput, with QMDB’s hybrid indexer still offering a speedup for DRAM-constrained setups. Table 3:QMDB is up to 8× faster than NOMT.Results are normalized by multiplying the transactions per second by the number of state updates per second. 4.3Reaching 2M updates per second We show preliminary results indicating that QMDB can double its throughput and reach 2 million updates per second by incorporating asynchronous I/O (io_uring) and direct I/O (O_DIRECT), improving CPU efficiency and eliminating VFS-related overhead respectively. Continuous advancements in SSD performance have resulted in modern consumer-grade SSDs (e.g., Crucial T705, Samsung 980 [ 11 ]) being able to reach over 1 million IOPS with only one drive. These high-IOPS SSDs are not yet available on AWS, so we approximate the performance in our preliminary experiments by using RAID0. After populating QMDB with 14 billion entries, we measured 2.28 million updates/second on i8g.metal-24xl (6 SSDs) and 697 thousand updates/second on i8g.8xlarge (2 SSDs), which are promising early results. 2.28 million updates is sufficient to support over one million native token transfers per second (each transfer requiring two state updates). QMDB’s CPU utilization averages 77% on the 32-core AWS i8g.8xlarge instance and 58% on the 96-core AWS i8g.metal-24xl instance, indicating that with faster SSDs the bottleneck is no longer SSD IO but rather CPU and synchronization overheads. We also evaluated NOMT with a lower capacity of 1 billion entries on the same instances (i8g.metal-24xl and i8g.8xlarge), and observed a maximum of 60,831 updates/second. We acknowledge that comparing these numbers would not be fair given that NOMT is focused on supporting single-drive deployments, and RAID0 has different performance characteristics than a single SSD. We plan a more comprehensive evaluation with a single high-performance SSD once we are able to secure a testbed with the necessary hardware. 4.4Scaling up and down QMDB scales up to huge datasets and down to ultra-low minimum system requirements, enabling it to meet the needs of blockchains with the highest (performance-oriented) and lowest (most decentralized) node requirements. Scaling up to hundreds of billions of entries. The hybrid indexer trades off SSD capacity and system throughput to reduce the DRAM footprint of the QMDB indexing layer to just 2.3 bytes per entry, allowing servers with a high ratio of SSD capacity to DRAM capacity to scale to huge world states. Table LABEL:table:eval:aws-datasize shows the maximum theoretical number of entries that can be stored in QMDB running on various different AWS instances. We calculate that the i3en.metal instance with high SSD capacity and a reasonable amount of DRAM could scale to 280 billion entries, far exceeding the needs of any existing production blockchain. Due to the prohibitive amount of time necessary to populate hundreds or even tens of billions of keys, we only run experiments up to 15 billion entries and conservatively extrapolate the results. The average DRAM overhead actually drops as more entries are inserted; 1 billion entries cost about 3 bytes of DRAM per entry, which drops to just 2.2 bytes per entry for 15 billion entries, indicating that the marginal DRAM overhead per additional entry is close to constant. Table 4:QMDB can scale to hundreds of billions of entries.The hybrid indexer uses only 2–3 bytes of DRAM per entry. *This table shows extrapolated theoretical world state sizes for different hardware configurations, and compares the maximum entries stored using the in-memory indexer vs the hybrid indexer. Scaling down to consumer-grade budget servers. We built a low-cost Mini PC (parts totaling about US$540 as of November 2024) to test QMDB under resource-constrained conditions. The system featured an AMD R7-5825U (8C/16T) processor, 64 GiB DDR4 DRAM, and a TiPro7100 4 TB NVMe SSD rated at approximately 330K IOPS. Despite these modest specs, QMDB achieved tens of thousands of operations per second with billions of entries. Using the in-memory indexer configuration, we were able to achieve 150,000 updates per second up to 1 billion entries, and stayed above 100,000 updates per second as we inserted up to 4 billion entries. With the hybrid indexer, QMDB maintained 63,000 updates per second storing 15 billion entries. These results highlight QMDB’s ability to operate on commodity hardware, improving decentralization by lowering the capital requirements and infrastructural barriers blockchain participation. 5Discussion Spatial locality is reduced in QMDB compared to general-purpose key-value stores such as RocksDB. It is true that QMDB does not preserve temporal locality, given that keys that were originally inserted at similar times can become separated in QMDB if they are later updated. However, this is not a disadvantage for blockchain workloads, given that blockchain infrastructure must assume worst-case workload characteristics to avoid exposing the blockchain to denial-of-service attacks in a Byzantine fault model. This is unlike traditional computing workloads which can rely on locality for average-case performance. In fact, most blockchains implement measures to uniformly distribute keys across storage with some exceptions (e.g., arrays in EVM); this already reduces or eliminates spatial locality. Provable historical state enables new applications such as a TWAP (Time-Weighted Average Price) aggregation at the tip of the blockchain with arbitrary time granularity. Peer-to-peer syncing of state can be easily and efficiently implemented by sharing state at the twig granularity. A downloaded twig accompanied by the inclusion proof of this twig against the global Merkle root can be inserted into the state tree independent of other twigs. Memory-efficient indexers are useful for heavily resource-constrained use cases or for decentralization of blockchains with tens of billions of keys. We implemented a memory-efficient SSD-optimized hybrid indexer that uses only 2.3 bytes per key but requires one additional SSD read per lookup. The hybrid indexer stores key-to-file offset mappings in immutable SSD-resident log-structured files and implements an overlay layer to manage entries in the SSD that have gone stale due to updates. In addition, the hybrid indexer uses a DRAM cache of the spatial and temporal locality of the application workload. State bloat is one of the many problems plaguing modern blockchains–as blockchains see growth in widespread adoption, world state is continuously growing to the point that it limits the ability of non-professional users to adequately run the validator software. QMDB achieves a memory footprint that is an order of magnitude smaller than existing verifiable databases, and using the hybrid indexer can further reduce the memory footprint and decrease barriers to validator participation. Recovery after failures (crash, blockchain reorganization) is done via replaying up to the last checkpoint and then trimming inactive entries. The reference QMDB implementation intentionally omits specific reorg optimizations and leaves it up to individual blockchains, given the variation in consensus protocols between different chains. QMDB can be extended to support quick switches with an undo log, but in general QMDB expects blockchains to build a buffering layer on top of QMDB and only write finalized data (which is a similar approach to other verifiable databases). Trusted Execution Environments (TEEs) offer several security advantages to blockchains, and to the best of our knowledge QMDB is the first TEE-ready verifiable database. Running a blockchain full node in a TEE (e.g., Intel SGX) protects the validator’s private key from leaking, provides a secure endorsement that the state root was generated by a particular binary, guarantees peers that the validator is non-byzantine, and prevents censorship. Current TEEs protect the integrity of CPU and DRAM, but cannot fully isolate persistent storage resources; QMDB protects its persistently stored data via AES-GCM [ 7 ] encryption using keys dynamically derived from the virtual file offset to protect against copy attacks. Zero-knowledge (ZK) proof generation for state transitions is increasingly seen as a crucial part of future blockchains, with one barrier to adoption being the long proof generation time. The generation of ZK proofs can be parallelized per state commitment [ 20 ] (e.g., each block can be proven individually and then chained together); thus, the degree of parallelization depends on the frequency of state root generation. QMDB’s high performance in-memory Merkleization is capable of computing a new state root per-transaction if desired, enabling the maximum degree of parallelism for ZK proof generation. 6Conclusion QMDB represents a significant leap in blockchain state databases, providing an order of magnitude improvement in throughput over state-of-the-art systems in datasets 10× larger than Ethereum at the time of writing. Organizing and compressing state updates into append-only twigs, QMDB is able to update and Merkleize world state with minimal write amplification, improving performance and reducing cost through efficient utilization of SSD IOPS. The immutability of full twigs allows state to be compressed by more than 99.9% for Merkleization, making it the first live-state management system capable of performing fully in-memory Merkleization with zero disk IO on a consumer-grade machine. We demonstrate that with these architectural innovations, QMDB can achieve up to 2 million updates per second and scale to world states of 15 billion keys. QMDB achieves lower minimum hardware requirements for all throughput benchmarks and world state sizes, democratizing blockchain networks by enabling affordable home-grade setups (US$540) to participate in large blockchains. At the same time, it provides substantial cost savings for large-scale operators due to its flash-heavy design that eliminates the need for large amounts of expensive and power-hungry DRAM. QMDB implements many new features not present in other ADSes, such as historical state proofs, opening opportunities for a new class of applications not yet seen on the blockchain. These features, together with order-of-magnitude advancements in performance and efficiency, establish QMDB as a breakthrough in scalable and verifiable databases. 7Acknowledgments We gratefully acknowledge the invaluable feedback and assistance provided by the many individuals and teams who helped refine our system. In particular, we thank Patrick O’Grady from Commonware for his expertise and guidance throughout the development of QMDB and the writing of this paper. We also extend our gratitude to Yilong Li and Lei Yang from MegaETH, and Ye Zhang from Scroll, for their insightful review of our design and manuscript. Finally, we thank Robert Habermeier and the Thrum team for their support in conducting the NOMT benchmarks. References [1]↑Reproducing benchmark numbers. https://github.com/thrumdev/nomt/issues/611 . [2]↑Amazon Web Services.Amazon Quantum Ledger Database (QLDB), 2019. 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[22]↑Todd, P.Merkle mountain ranges. https://github.com/opentimestamps/opentimestamps-server/blob/master/doc/merkle-mountain-range.md , 2016.Accessed: 2024-11-18. [23]↑Wood, G.Ethereum: A secure decentralized generalized transaction ledger.In Ethereum Yellow Paper (2014). [24]↑Yang, X., Zhang, Y., Wang, S., Yu, B., Li, F., Li, Y., and Yan, W.Ledgerdb: A centralized ledger database for universal audit and verification.Proceedings of the VLDB Endowment 13, 12 (2020), 3138–3151. [25]↑Yue, C., Dinh, T. T. A., Xie, Z., Zhang, M., Chen, G., Ooi, B. C., and Xiao, X.Glassdb: An efficient verifiable ledger database system through transparency.arXiv preprint arXiv:2207.00944 (2022).
Shanghai taps Taylor Swift to grow China’s economy
The entertainment industry is stepping up for China’s economy in a week that has been dominated by conversations about TikTok and potential alternative apps and investments. The focus has shifted to the American music icon, Taylor Swift. Shanghai has begun preliminary conversations with the singer and songwriter about organizing a concert this year. The agenda by Chinese cities aims to attract international celebrities and stimulate the economy. According to reports, Zhang Qi, the deputy director of Shanghai’s culture and tourism bureau, stated that local officials had hosted Swift’s team for preliminary discussions in the municipality. In a statement, he said, “As for whether it will ultimately happen, it depends on the market and the attractiveness of our city. However, we are optimistic and think that there may be hope for this year.” The report was released one month after Swift ended her Eras Tour. The tour set a new record, with the final performance in Vancouver, Canada. The estimated global economic impact was within the remarkable range of $13 to $28 billion, with 10.1 million fans attending 149 events. Now, the second-largest economy in the world is set to step up and allow entertainment to work for it. It will follow in the footsteps of the United States, which has made the most of its entertainment industry. The demand for international performances in China In recent years, Shanghai has become a thriving center for cultural events. The city has hosted several large-scale commercial performances. To that end, there has also been a significant increase in the demand for live performances. The capital is frequently the initial destination for international celebrities during their mainland China tours. See also China's desperate push to stabilize the yuan is only making things worse Apparently, Japan and Singapore were the sole Asian destinations on Swift’s record-setting Eras Tour. The concert documentary Taylor Swift: The Eras Tour, which was released globally in October 2024, was the highest-grossing music documentary in Chinese Box Office history. The movie screened in China for 69 days, attracting over 2 million viewers and grossing 100 million yuan ($13.8 million). Additionally, local officials are placing their expectations on live music performances to stimulate their economies. This is prompting other Chinese cities to compete for the opportunity to host renowned singers. Tourism and consumer spending are driven by the willingness of many fans, particularly the youth, to travel to other cities for major concerts. For instance, last month, a tourism official in Hangzhou, China, expressed anticipation that Swift would perform in his country. This happened after British artist Ed Sheeran confirmed his intentions to play six gigs in Hangzhou in February and March, the only Chinese stop on his next tour. Also, this year, the southern island province of Hainan has extended an invitation to rap superstars such as Travis Scott and Cardi B to perform. See also Janet Yellen says president Biden's policies made US economy stronger Notably, two sold-out Kanye West concerts in Hainan in September generated an estimated 700 million yuan ($95.5 million) in tourism revenue. Other Western megastars who have visited China lately include American singer Mariah Carey, who played two gigs in Beijing in September. In October, John Legend performed in Beijing and Shanghai, while in December, British artists Jessie J and James Blunt performed in several locations around China. China’s government to loosen regulations on international acts The process of hosting international performances in China is complicated and requires the ability to navigate a complex web of regulations and restrictions. In the past, the Chinese government has been hesitant to allow big events. Most especially ones with foreign singers, out of fears that they would change Chinese culture and threaten public safety. However, advisers to the Shanghai government referred to celebrities like Swift as “walking GDP” due to their tremendous economic influence. They advocated for lesser limitations on international performers in order to stage more high-profile shows. As a result, the Shanghai municipal government’s counselors’ office posted on its social media account that government departments should simplify the process of obtaining visas, approvals, and customs in order to attract top-tier talent. Land a High-Paying Web3 Job in 90 Days: The Ultimate Roadmap
Bitget pre-market trading: Jambo (J) is set to launch soon
We're thrilled to announce that Bitget will launch Jambo (J) in pre-market trading. Users can trade J in advance, before it becomes available for spot trading. Details are as follows: Start time: 15 January, 2025, 15:00 (UTC) End time: 22 January, 2025, 09:30 (UTC) Spot Trading time: 22 January, 2025, 10:00 (UTC) Delivery Start time: 22 January, 2025, 11:00 (UTC) Delivery End time: 22 January, 2025, 23:00 (UTC) Pre-market trading link: J/USDT Bitget Pre-Market Introduction Delivery method: Coin settlement, USDT settlement Coin settlement Starting from the project's delivery start time, the system will periodically execute multiple deliveries for orders under the Coin Settlement mode. Sell orders with sufficient spot balances will be filled with corresponding buy orders. If there are insufficient project tokens or if sellers voluntarily choose to default, compensation with security deposits will not be triggered immediately. At the project's delivery end time, the system will either deliver or compensate any remaining undelivered orders. USDT settlement For orders under the USDT Settlement mode, all delivery will be executed at the delivery end time of the project. The delivery time for the pre-market project will be announced once the coin's spot listing time is confirmed. Stay tuned to relevant notifications and announcements for the latest information. Example: The user buys 10 tokens at 10 USDT (the filled order is called Order A) and sells 10 tokens at 15 USDT (the filled order is called Order B). At delivery time, the system calculates the delivery execution price based on the average index price from the last minute. Assuming the execution price is 5 USDT, the calculations are as follows: PnL of Order A = (5 – 10) × 10 = –50 USDT PnL of Order B = (15 – 5) × 10 = 100 USDT The total PnL for the user in pre-market trading is 50 USDT. For USDT settlement, orders are settled at the average index price from the last ten minutes as the delivery execution price, determined by a weighted average of prices at leading exchanges to ensure fairness and transparency. Introduction Jambo is building a global on-chain mobile network, powered by the JamboPhone — a crypto-native mobile device starting at just $99. Jambo has onboarded millions on-chain, particularly in emerging markets, through earn opportunities, its dApp store, a multi-chain wallet, and more. Jambo’s hardware network, with 700,000+ mobile nodes across 120+ countries, enables the platform to launch new products that achieve instant decentralization and network effects. With this distributed hardware infrastructure, the next phase of Jambo encompasses next-generation DePIN use cases, including satellite connectivity, P2P networking, and more. At the heart of the Jambo economy is the Jambo Token ($J), a utility token that powers rewards, discounts, and payouts. J Total supply: 1,000,000,000 Website | X | Telegram FAQ What is pre-market trading? Bitget pre-market trade is an over-the-counter trading platform specializing in providing a pre-traded marketplace for new coins before their official listing. It facilitates peer-to-peer trading between buyers and sellers, enabling them to acquire coins at optimal prices, secure liquidity in advance, and complete delivery at a mutually agreed upon time. What are the advantages of Bitget pre-market trading? Investors often have expectations regarding the price of a new coin before spot trading becomes available. However, they may be unable to purchase the coin at their preferred price and secure liquidity in advance due to lack of access. In response to this, Bitget pre-market trading offers an over-the-counter (OTC) platform where buyers and sellers can establish orders in advance to execute trades as desired and complete delivery later. In this scenario, sellers are not required to own any new coins; instead, they only need to obtain sufficient new coins for delivery before the designated delivery time. How are pre-market trades deliveries completed? Coin Settlement orders: Sellers can choose to either deliver the tokens or compensate with security deposit before the delivery execution. Starting from the project's delivery start time, the system will periodically execute multiple deliveries for orders under the Coin Settlement mode. Sell orders with sufficient coin balances will be filled with the corresponding buy orders. If there are insufficient project tokens or if sellers voluntarily choose to default, compensation with security deposits will not be trigger immediately.At the delivery end time of the project, the system will settle all remaining orders, either through buy delivery or compensation. If there is a sufficient balance, the corresponding quantity of tokens will be transferred to the buyer's spot account, and the buyer's frozen funds will be transferred to the seller's spot account as payment. Otherwise, the transaction will be canceled. In this case, the system will unfreeze the buyer's funds and compensate the buyer with the seller's frozen security deposit. USDT Settlement orders: All deliveries will be executed at the project's delivery end time. Orders are settled at the average index price over the last ten minutes, which serves as the delivery execution price. Profits and losses are calculated based on the difference between the execution price and the delivery execution price. The losing party will pay the difference to the winning party. Note: 1) The system will execute deliveries in chronological order based on the transaction time of the orders. If you have both buy and sell orders in Coin Settlement mode, the quantities cannot offset each other. Please ensure that your spot account has a sufficient available balance for the sell orders at the time of delivery. Orders with insufficient balance will be treated as the seller's default. 2) For coin settlement orders, only tokens available in your spot account will be used for delivery. Tokens frozen in pending orders or held in other accounts will not be used for delivery. 3) The delivery is expected to be completed within one hour. To mitigate the risk of delivery failure due to insufficient funds, the seller of coin settlement orders should refrain from any transactions involving the delivery currency within 30 minutes after the delivery initiation. How can I make a pre-market trade as a seller? As a seller, you are required to use the USDT in your spot account to pay the margin. You can list your new tokens on the order market at your preferred price via Post Order, or you can find a suitable buy order on the order market and sell it to the buyer at the buyer's asking price. Once the order is filled, you just need to wait for the delivery. How can I make a pre-market trade as a buyer? As a buyer, you are required to use USDT from your spot account to pay for the trade. Using the Place Order function, set the quantity of coins you want to buy at your preferred price and list the maker order in the order market. Bitget will then lock the funds for the purchase and handle any related fees. Alternatively, you can directly select a sell order from the marketplace and buy the coins at the seller's designated price. Once the order is filled, simply await delivery. Do I have to fill the entire maker sell/buy order at once in pre-market trading? No, the platform allows you to trade any quantity of coins as long as it meets the minimum transaction limit. Disclaimer Cryptocurrencies are subject to high market risk and volatility despite high growth potential. Users are strongly advised to do their research as they invest at their own risk. 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Countdown to departure! SEC Chairman Gary Gensler accepts a public interview, addressing 11 key questions about cryptocurrency and the capital markets
Author: Weilin, PANews Only 6 days remain until Donald Trump is inaugurated as the President of the United States. On January 14, Gary Gensler, the Chairman of the Securities and Exchange Commission (SEC), gave consecutive interviews to CNBC and Yahoo Finance, where his leadership style and policy legacy became hot topics of discussion. Previously, Gensler announced that he would resign from the SEC chairmanship on January 20. Based on these two interviews, PANews has compiled 11 important questions regarding cryptocurrency and capital markets, along with Gensler's responses. 1. On January 14, the SEC took action against Robinhood and some private equity firms. With less than a week left in your term, can we expect more actions from the SEC? We are entrusted by the public to ensure that the capital markets operate for them, protect investors, and ensure compliance with the law. We have an important responsibility and will fulfill that responsibility, regardless of who is in leadership. There will be a transition of leadership this week and next, but we will continue to ensure that the capital markets serve investors and that market participants comply with the law. That is our job. Essentially, how can we build trust in the capital markets if we do not adhere to the facts and the law? In fact, honest actors in the market will benefit because more investors will be willing to enter and participate in the market. 2. What do you think the next administration means for the SEC? Are you concerned that what you have done during your term will be overturned by the next administration? The achievements we have made during this administration are significant. I took office after the GameStop incident, during a peak period for special purpose acquisition companies (SPACs), and we implemented some of the most important reforms in the stock market. I would say that we, along with other commissioners, completed this reform in a unanimous and bipartisan manner. We also made significant reforms in the treasury market. I cannot imagine anyone wanting to revert to longer settlement periods when we have shortened the settlement period to one day. I also cannot imagine anyone wanting to withdraw the first federal privacy notice to the public, which states that if your information is leaked by an investment advisor or broker, you will be notified. I dare say that I do not think anyone would want to roll back these measures. They would not make it easier for insiders to trade on significant non-public information. So, I am very satisfied with the work we have done. Of course, democracy has its outcomes, and the next team may choose a different direction, but I believe these are all good policies that reduce costs and promote integrity in the capital markets. 3. Some people believe that cryptocurrency supporters helped Trump win the latest election. How do you respond to these views? Building trust in the capital markets is important, and people need to comply with the laws passed by Congress, and this great institution is responsible for enforcing those laws. Think about this issue: we have rules on the highways, we have traffic lights, and we have police officers. If you are driving a hybrid car on the highway, does it not need to follow traffic laws? Or does an electric car not need to follow the rules on the highway? We enforce the law consistently in the financial markets, and the cryptocurrency space is not compliant. I would also say that voters are smart enough to know that they vote based on other issues, such as inflation or other economic matters. I have not seen any evidence that cryptocurrency was a major factor influencing voter decisions. 4. You have achieved many accomplishments during your term, including shortening the settlement period and reforms in money market funds and the treasury market. However, you lost 4 out of 5 challenges to your rules, a number that exceeds the total of the previous three chairs. Is there anything you wish you could have done differently? For anyone working in government, this is an interesting time because the courts are undergoing significant changes. The great hockey player Wayne Gretzky once said something along the lines of, you should skate to where the puck is going, not to where it has been. The courts here are like the puck; where are they heading? They are reinterpreting the law, whether it is environmental law, communications law, health law, or securities law. We have been acting in accordance with the law, working based on the laws passed by Congress. We have established 46 rules that are very important to the capital markets, the vast majority of which have not only been passed but are also being implemented. So, people can now benefit from these rules, such as knowing whether company executives received compensation based on erroneous financial reports and whether that information needs to be clawed back. As you mentioned, we have made reforms in the money market space, but at the same time, the SEC can now obtain better information about private funds. So we have achieved a lot together. 5. You have repeatedly warned about the risks of cryptocurrency. Over the past year, the courts have somewhat forced you to approve spot Bitcoin and Ethereum ETFs, opening up cryptocurrency investments to the public. Do you wish for a different outcome? Are investors facing greater risks as a result? Bitcoin itself is not a security; neither I nor my predecessors have said that Bitcoin is a security, nor have we said that Ethereum is a security. I believe that investors in Bitcoin and Ethereum, including the general public you mentioned, had opportunities to invest long before the ETF products. Approving a Bitcoin ETF during my term was a spot ETF, which was launched later. Investors in spot trading products are better protected, with lower fees, stricter regulation, market monitoring, and these products are registered in compliance with SEC requirements. My predecessors had rejected these products, while we followed the leadership approach of J. J. Clayton. Bitcoin and Ethereum account for 70% to 80% of the cryptocurrency market. What I am really concerned about is the other parts, those thousands of tokens, which continue to exist on the condition that investors are essentially investing, or betting on a project, and they need to receive appropriate disclosures. The law requires that you should receive such disclosures, but currently, these tokens are not compliant. I do not prejudge any particular project. 6. You seem to intend to separate Bitcoin from the rest of the industry. Have you begun to have a new view of Bitcoin? Do you think Bitcoin has intrinsic value and serves as a store of value? Or do you think that in 10, 15, or 20 years, looking back, it will be seen as the tulip bubble of the 18th century? You have taught at MIT, so you should have some insights. Have you read the book "The Bitcoin Standard"? It is hard to predict. I know how you view these other coins, and I know you have a negative perspective. But as for Bitcoin, the SEC has never said it is a security. Yes, (I have read it), and I believe Bitcoin is a highly speculative and volatile asset. But there are 7 billion people in the world, and everyone wants to trade it. Just as we have had gold for 10,000 years, we now have Bitcoin, and perhaps in the future, there will be other similar things. These thousands of other projects need to demonstrate their use cases and prove they have real fundamentals; otherwise, they will not be sustainable. 7. Do you not like those other coins? I have never owned those coins, and I have maintained that stance for 7 or 8 years. 8. How do you view the concept of prediction markets, especially the decision by Kalshi to hire Trump's son as an advisor? I have no opinion on who others hire. But the capital markets themselves are vast, with a $120 trillion capital market, whether it is stocks, bonds, or ultimately prediction markets, it is all about predicting future cash flows or forecasting future opportunities for businesses. Therefore, these markets, in a sense, are all about prediction markets, which is also why I am proud of some of the reforms we have implemented. We have established better information disclosure to ensure that only meaningful information is disclosed to investors so they can make their own judgments about the future based on that information. 9. Critics argue that the SEC relies too much on litigation rather than legislation. What do you think? We have laws. Congress has passed these laws, and of course, they can change. But part of the cryptocurrency space involves the public investing based on these projects, many of which are regulated by securities laws. In this space, many companies have not complied with the regulations. Most of what you discuss daily revolves around stocks, bonds, or a combination of market fundamentals, valuations, and sentiment. However, the cryptocurrency space seems to rely more on sentiment, with much less in terms of fundamentals. But if there are fundamentals, and I say if, then appropriate disclosures need to be made under securities laws. That is the basic trading rule. 10. What do you think is the biggest risk in the current market? We are currently in a presidential transition period, and democracy has been reflected. Certain policies will become clearer over time, but there is certainly uncertainty in policies. Over the past four years, I have also mentioned that there are areas in the capital markets with a lot of leverage, a lot of borrowing, and low margins. Typically, these issues arise in the so-called repo market where commercial banks provide leverage to macro hedge funds. Ultimately, I believe that artificial intelligence has transformed productivity and positively impacted various fields, but there are still some risks in the future. 11. If you could do it all over again, what different decisions would you make? I wish we could have completed these reforms in the treasury and stock markets earlier, and that the related issues with the courts could have been handled more smoothly. It is worth noting that the attitude of the courts is undergoing dramatic changes. I really wish I could better predict these changes so that we could do things that would better respond to the challenges posed by the courts.
Learn2Earn: Take the Jambo (J) Quiz to grab a Share of 32,700 J!
Jambo is building a global on-chain mobile network, powered by the JamboPhone — a crypto-native mobile device starting at just $99. Jambo has onboarded millions on-chain, particularly in emerging markets, through earn opportunities, its dApp store, a multi-chain wallet, and more. Jambo’s hardware network, with 700,000+ mobile nodes across 120+ countries, enables the platform to launch new products that achieve instant decentralization and network effects. With this distributed hardware infrastructure, the next phase of Jambo encompasses next-generation DePIN use cases, including satellite connectivity, P2P networking, and more. At the heart of the Jambo economy is the Jambo Token ($J), a utility token that powers rewards, discounts, and payouts. Promotion period: 16 January, 10:00 - 22 January, 10:00 (UTC) Activity 1: Complete the quiz and grab a share of 16,700 J! Read the introduction. Correctly answer all questions in the Learn2Earn quiz. Airdrop: 2 J Activity 2: New user airdrop — grab a share of 16,000 J! Sign up for a Bitget account and correctly answer all Learn2Earn quiz questions during the promotion. Complete a spot trade of any amount. Airdrop: 4 J *You can take the Learn2Earn quiz only once a day during the promotion until you answer all questions correctly. Read the introduction carefully and answer the questions. Terms and conditions Airdrops are limited, so don't miss out! Airdrops will be distributed to the winners' accounts within seven working days after the end of the promotion. Bitget reserves the right to disqualify users engaging in wash trading, mass registration of accounts, or trades that exhibit signs of self-dealing or market manipulation. Accounts with the same IP address will not be eligible for airdrops. Bitget reserves the right of final interpretation of the terms and conditions of this promotion, including but not limited to changes, amendments to the promotion rules, or the cancellation of the promotion without prior notice. Contact us if you have any questions. Disclaimer Cryptocurrencies are subject to high market risk and volatility despite high growth potential. Users are strongly advised to do their research as they invest at their own risk. Thank you for supporting Bitget! Join Bitget, the World's Leading Crypto Exchange and Web 3 Company Sign up on Bitget now >>> Follow us on Twitter >>> Join our Community >>>
Jambo: Token J to be launched on Solana chain in January
Web3 mobile infrastructure provider Jambo announced that it will launch J tokens on the Solana chain in January with a total supply of 1 billion tokens, with the aim of creating the first mobile-first ecosystem powered by J tokens.
Jambo Partners with Solana and Tether to Bring Mobile Blockchain Technology to Emerging Markets
Original source: Jambo Jambo, the world’s largest Web3 mobile infrastructure provider, announced its official entry into Solana and joined hands with Tether to bring customized blockchain financial and education technology solutions to emerging markets. Jambo’s core product, the JamboPhone, a $99 Web3 smartphone, has successfully attracted a variety of user groups to the chain with its mobile-first strategy. With Solana’s high processing power and USDT’s market dominance, Jambo will provide access to a wider range of Web3 financial and education products in regions such as Southeast Asia, Africa, and Latin America, allowing these technologies to benefit those who need them most. About JamboPhone The JamboPhone, priced at only $99, is already sold in more than 120 countries around the world. It is designed for Gen Z consumers in emerging markets as a window for them to explore the world’s top digital products and services. Users can easily integrate into the global economy through the pre-installed Jambo ecosystem applications covering DeFi, games, and Web3 infrastructure. JamboPhone is committed to solving major challenges facing emerging markets, such as large populations lacking banking services and limited access to smartphones. Users can purchase JamboPhone through SolanaPay at JamboPhone.xyz . Jambo App: A New User Empowerment Experience JamboPhone has a built-in one-stop Web3 platform - Jambo App, which provides a variety of services including DeFi, games and educational content, all designed for the needs of users in emerging markets. The Jambo App also has built-in Jambo Wallet, a non-custodial multi-chain wallet that supports Solana tokens and USDT stablecoins. Jambo mainly distributes rewards through USDT. With its wide recognition and stability in emerging markets, users can participate in various tasks provided by Jambo and its ecosystem partners, from educational projects to promotional activities. Rewards are now mainly distributed in the form of SPL USDT. This program highlights the pioneering role of Jambo, Solana and Tether in narrowing the digital divide, committed to making digital financial tools more popular, while creating income opportunities for users in emerging markets. Leveraging the power of the local Solana community Jambo will also work with local Superteams to promote the rapid adoption of Web3 technology. Superteams are a global community of Web3 builders who are passionate about Solana technology and aim to help Web3 talent learn new knowledge, earn income, and connect with the Solana ecosystem. These teams, composed of local experts and passionate supporters, play a vital role in educating the community, promoting local development, and driving grassroots activities for sustainable growth within the Web3 ecosystem. Lily Liu, President of the Solana Foundation, said, "Back in 2017 when I was building earn.com, our dream was to create a product where 'anyone with a mobile phone can have a job.' Alice, James and the Jambo team have made this dream a reality by building Web3 mobile infrastructure and paving the way for financial access in emerging markets. Jambo provides an easily accessible Web3 portal for almost everyone in the world, and Solana enables almost everyone with Internet access to financial services. Together, we are committed to enabling millions of people to easily access self-asset custody, financial opportunities, and educational resources." Why focus on emerging markets Emerging markets have a unique set of economic challenges, and Solana and Tether provide a way to address them with their blockchain and stablecoin solutions. In these markets, USDT usage far exceeds that of other stablecoins, with over 34.2 million unique wallets adopting USDT as of April 2024, a large user base that reflects Tether’s trust and popularity in emerging markets. Jambo’s revolutionary smartphone combines Solana’s fast transaction processing capabilities, low transaction fees, and Tether’s stable and broad user base, giving users access to stablecoin and cryptocurrency payment channels, alternative banking services, and global profit opportunities. "Our goal is to bring emerging markets into the on-chain environment," said James Zhang, co-founder of Jambo. "By combining with Solana and Tether, Jambo is able to provide a comprehensive set of solutions to meet the special needs of these regions." Later, Paolo Arodino, CEO of Tether, also said, "Emerging markets have great potential for financial inclusion, and their demand for tools such as USDT has driven our determination to create a brighter financial future for users in these regions. By providing Web3 technology at a reasonable price through JamboPhone and leveraging the power of the Solana blockchain, Jambo is empowering users in these regions with the tools they need to participate in the global digital economy. The integration of SPL USDT as a reward mechanism further consolidates this plan and provides users with a stable and secure digital asset." To learn more about Jambo at X , visit this website to purchase a JamboPhone. Join the Jambo community and lead Web3 with us on Telegram . About Jambo Jambo aims to bring emerging markets into the blockchain era by building the world's largest Web3 mobile infrastructure network. Jambo is backed by top global investors including Paradigm, Tiger Global, Pantera, Delphi, and more. Jambo is using the JamboPhone smartphone to introduce the next billion users to the world of Web3, starting at $99. This phone comes pre-installed with a rich set of Web3 applications, allowing users to easily experience the convenience of Web3. The pre-installed Jambo ecosystem includes Web3 mobile games, digital wallets, payment infrastructure, and more features will be launched in the future. This article comes from a contribution and does not represent the views of BlockBeats
Jambo is joining Galxe's GAL Staking ecosystem and is about to release snapshot rules
News on June 28, Galxe announced on the X platform that Web3 mobile infrastructure Jambo has joined its GAL Staking ecosystem and will soon release snapshot rules and time announcements.
Network3 and Jambo Phone have reached a strategic cooperation to jointly promote the popularization of DePin technology
According to ChainCatcher, Network3 has reached a cooperation with Jambo Phone, a Web3 mobile phone. This cooperation will promote the integration of Network3 and Jambo Phone. Network3 dApp will be available on Jambo Phone, enabling millions of users in emerging countries to participate in Network3's DePin and Edge AI construction. It is reported that Network3 builds AI Layer2 to help global AI developers quickly and conveniently train or verify models on a large scale. Jambo Phone is a new product launched by Jambo in February this year in conjunction with the Aptos Foundation. It aims to promote Web3 access in emerging markets.
Aptos Foundation and Jambo launch JamboPhone, priced at $99
The Aptos Foundation teamed up with Web3 application Jambo to launch JamboPhone, priced at $99, and is now available for sale in more than 40 countries/regions. The aim is to promote Web3 access in emerging markets. JamboPhone comes pre-installed with the Aptos ecosystem wallet Petra and JamboApp, providing direct access to the Aptos ecosystem and other ecosystems.
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