The Evolution and Future Prospects of Blockchain Data Indexing Technology

1. Introduction

The development of Blockchain technology has led to the rise of a large number of decentralized applications ( dApp ). From the initial simple games and financial applications on Ethereum to today's complex cross-chain ecosystems, the data demands of dApp are also continuously increasing. At the same time, breakthroughs in Artificial Intelligence ( AI ) technology have brought new possibilities for the processing and application of blockchain data. This article will explore the development history of blockchain data indexing technology and how AI technology is bringing innovation to this field.

2. From Blockchain Nodes to Full Chain Database

2.1 Data Source: Blockchain Node

Blockchain nodes are the foundation of the entire network, responsible for recording and storing all transaction data. However, ordinary users find it difficult to maintain nodes, which has led to the emergence of RPC node providers. Although RPC services lower the barrier to data access, there are still efficiency issues in complex queries.

2.2 Data Parsing: From Raw Data to Usable Information

Blockchain raw data is typically encrypted and encoded, requiring a specialized parsing process to be transformed into understandable and usable information. The quality of data parsing directly affects the effectiveness of subsequent applications.

2.3 Evolution of Data Indexers

As the amount of data increases, the demand for indexers is growing. Indexers simplify the data retrieval process by organizing on-chain data and providing a unified query interface. Different types of indexers each have their advantages, providing solutions for specific scenarios, from full node indexing to dedicated indexers, and then to aggregation indexers.

2.4 Full-Chain Database: Stream-First Approach

Traditional indexing methods struggle to meet complex query demands, prompting the industry to move towards real-time data streams. This shift enables organizations to quickly respond to data changes and provide more comprehensive query capabilities.

3. The Combination of AI and Databases: A Comparison of The Graph, Chainbase, and Space and Time

3.1 The Graph

The Graph provides multi-chain data indexing and querying services through a decentralized network of nodes. At its core is the subgraph (Subgraphs) concept, which defines the way data is extracted and transformed. Indexers, curators, delegators, and developers in the network together form a complete ecosystem. The Graph has also been actively introducing AI technologies recently, such as tools like AutoAgora and AgentC, to enhance the intelligence level of the system.

3.2 Chainbase

Chainbase, as a full-chain data network, integrates multi-chain data and provides real-time data lake services. Its features include a dual-chain architecture, innovative data format standards, and an AI-enabled cryptographic world model. Chainbase's AI model Theia can deeply mine the value of on-chain data, providing users with intelligent services.

3.3 Space and Time

Space and Time (SxT) is dedicated to building a verifiable computing layer, with its innovative Proof of SQL technology providing zero-knowledge proof support for data queries. SxT has also collaborated with Microsoft's AI Lab to develop natural language processing tools, simplifying user queries on Blockchain data.

Conclusion and Outlook

The blockchain data indexing technology has evolved from simple node data sources to AI-powered full-chain services, experiencing significant progress. In the future, with the development of technologies such as AI and zero-knowledge proofs, blockchain data services are expected to become further intelligent and secure, providing a solid foundation for industry innovation.