Recently, the launch of @SpaceandTimeDB on Binance has caused widespread discussion in the market, and for a time it has ignited the previously relatively unpopular narrative direction of "ZK data infrastructure". As a bridge between smart contracts and off-chain data, $SXT is trying to solve a lower pain point in the on-chain world: trusted execution and verification of data. Next, let's talk about my observations: 1) Space and Time is essentially a decentralized one-layer blockchain (SXT Chain), but its core value is not to build a general smart contract platform, but to focus on solving a clear problem: to achieve trusted data processing under zero-knowledge proofs. Its killer feature, Proof of SQL, makes tamper-proof data tables no longer on paper, and realizes the verifiability of queries and the integrity of data through ZK technology. To put it another way, this is a complete reversal of the blockchain world's inherent thinking about how data is processed: in the past, smart contracts either endured the sky-high gas costs of on-chain storage or were forced to trust centralized APIs and oracles. SXT provides a third path: to build a dedicated decentralized data layer, combining on-chain cryptographic commitments and off-chain SQL execution, making data processing both secure and trustworthy, efficient and low-cost. 2) From the perspective of technical architecture, the SXT network consists of three key components: 1. Indexer Nodes: Acts as a data collector, responsible for obtaining real-time and historical data from mainstream blockchains and converting them into SQL relational formats; 2. Prover Nodes: It is responsible for the role of the computing engine, processing query requests, executing ZK-proven SQL queries on tamper-proof tables, and generating sub-second ZK proofs. 3. SXT Chain Validators: Equivalent to data notaries, maintaining network integrity, handling data insertion, and collectively endorsing on-chain cryptographic commitments through BFT consensus. This architecture enables on-chain storage to only hold cryptographic promises (similar to data fingerprinting), rather than complete data, which greatly reduces the cost of on-chain storage. What's more, these promises are updatable/homomorphic, which means that the data can be updated without recalculating the fingerprint of the entire dataset, and only needs to be overlaid on top of the original fingerprint – a key way to solve the performance bottleneck encountered by traditional ZK solutions in big data processing. 3) SXT's Proof of SQL is not only a technological innovation, but also solves the core pain points of the current ZK proof system when processing large-scale data: 1. Scalability: Traditional ZK proofs are inefficient in processing large data sets, while SXT claims to be able to generate ZK proofs in milliseconds, and if the on-chain verification gas consumption is as low as 150k, it will be a big breakthrough in the entire ZK Prove field. 2. Development-friendly: It provides a SQL interface that developers are familiar with, rather than complex ZK circuit programming, which significantly reduces the development threshold; 3. Versatility: It is not only applicable to SXT's own decentralized database, but also can be applied to traditional databases (such as PostgreSQL and Snowflake), expanding the scope of application of the technology. From the perspective of abstraction, SXT actually creates a "trusted data computing platform" for the blockchain world, breaking through the natural data blind spot of smart contracts and making on-chain applications no longer data silos. It is equivalent to a set of "query coprocessors", which solves the inherent limitations of smart contracts that cannot directly access historical on-chain data, cross-chain data, off-chain data, or complex aggregated data. 4) Aside from the technical narrative, the business value of SXT may be more noteworthy. Its application scenarios cover almost all the current hotspots of Web3: 1. ZK-Rollups/L2 optimization: as the data layer of L2, it reduces gas cost and enhances scalability. 2. Cross-chain security bridging: provide multi-chain data verification to enhance the security of the bridge; 3. Decentralized DApp backend: replace the traditional centralized backend and provide verifiable data services; In addition, it also includes data-driven DeFi, RWA, GameFi, and SocialFI and all other use cases that face on-chain storage bottlenecks. 5) Finally, let's take a look at the design of SXT's token economic model, which seems to me to have the charm of a traditional POS+ data market: 1. Validators: Stake SXT to participate in network security and obtain network fees and token emission rewards; 2. Table Owners: Create and maintain tamper-proof data tables, and profit from insertion fees and query fees. 3. Users: Pay the query fee to use the network service. The best part of this model is that the "query fee" is divided between data providers and validators, forming a self-driven data market ecology, the more valuable the data, the larger the query volume, and the more benefits all parties will benefit, so as to attract more high-quality data to enter the market and complete the positive cycle. Above. Overall, $SXT's biggest innovation value is that it has created a solution that combines SQL, a traditional database tool, with a Web3 zero-trust architecture, so that the blockchain ecosystem can handle more complex data logic. This not only makes up for the "innate data shortcomings" of smart contracts, but also provides a feasible path to the chain for enterprise-level applications that have strict requirements for data quality and processing capabilities. With the project's deep binding to leading ecosystems such as zkSync, Avalanche, and Chainlink, coupled with the golden sign of Binance, SXT already has a "ticket" to impact mainstream infrastructure. Of course, the challenges are also obvious, the technology still needs to overcome the natural contradiction between decentralization and performance, and it will take time for market education and developer adoption.