From Data Sources to Smart Services: Analyzing the Evolution of Blockchain Data Indexing

Introduction

The vigorous development of blockchain applications cannot be separated from the data support behind them. From the initial simple applications to the now diversified financial, gaming, and social platforms, every step of progress in the blockchain ecosystem relies on efficient and reliable data access mechanisms. In 2024, at the intersection of artificial intelligence and Web3, the importance of data is even more self-evident. This article will delve into the development history of blockchain data accessibility and conduct comparative analysis of several major data indexing protocols, with a special focus on how they integrate AI technology to provide innovative services.

The Evolution of Data Indexing: From Nodes to Full-Chain Database

Data Source: Blockchain Node

Blockchain nodes are the cornerstone of the entire network, responsible for recording, storing, and disseminating all on-chain transaction data. However, for ordinary users, maintaining a node not only requires high technical skills but also entails substantial hardware and bandwidth costs. To address this issue, RPC node providers have emerged, allowing users to access blockchain data without having to build their own nodes. Nevertheless, RPC services still exhibit lower efficiency when handling complex queries and have limited cross-network compatibility.

Data Analysis: Convert Raw Data

The raw data provided by blockchain nodes is often encrypted and encoded, making it extremely difficult for most users to use this data directly. The data parsing process converts these complex raw data into a more understandable and operable format, which is a key link in data applications.

Evolution of Data Indexers

With the explosive growth of Blockchain data, efficient data indexers have become indispensable. Indexers simplify the process for developers to obtain the necessary information by organizing on-chain data and providing a unified query interface. Different types of indexers, such as full node indexers, lightweight indexers, dedicated indexers, and aggregate indexers, each have their advantages, catering to different application scenarios.

Compared to traditional RPC endpoints, the indexer provides more efficient data retrieval and query capabilities, supports complex queries and cross-chain data aggregation, while enhancing the system's security and reliability.

Full Chain Database: Flow Priority Trend

As application demands become increasingly complex, the standardized format of traditional indexers is gradually unable to meet diverse query needs. The industry is moving towards building real-time Blockchain data streams to reduce latency and enhance responsiveness. This "stream-first" approach enables organizations to react to data almost in real-time, supporting a wider range of application scenarios and data analysis.

AI+Database: Comparison of The Graph, Chainbase, and Space and Time

The Graph

As a decentralized multi-chain data indexing and query service network, The Graph defines data extraction and transformation methods through subgraphs. The network is jointly maintained by indexers, curators, delegators, and developers, ensuring the system operates efficiently through economic incentives. Recently, The Graph ecosystem has introduced several AI tools, such as AutoAgora, Allocation Optimizer, and AgentC, further optimizing pricing strategies, resource allocation, and user experience.

Chainbase

Chainbase, as a full-chain data network, integrates multi-chain data and provides real-time data lake services. Its unique dual-chain architecture and innovative data format standard "manuscripts" enhance the programmability and composability of data. Chainbase's AI model Theia, based on on-chain and off-chain data, offers intelligent data analysis and insights.

Space and Time

Space and Time (SxT) is committed to building a verifiable computing layer, with its core innovation, Proof of SQL technology, ensuring the tamper-proof and verifiable nature of SQL queries on decentralized data warehouses. SxT has also collaborated with Microsoft AI Lab to develop natural language processing tools to simplify user interaction with Blockchain data.

Conclusion

Blockchain data indexing technology has evolved from the initial node data sources, through the development of data parsing and indexers, to ultimately an AI-enabled full-chain data service. This process not only improves the efficiency and accuracy of data access but also brings an intelligent experience to users. In the future, with advancements in AI technology and new technologies such as zero-knowledge proofs, blockchain data services will continue to support industry innovation as infrastructure and drive the development of the entire ecosystem.