🤖 AI Summary
High acquisition costs for on-chain blockchain data and expensive commercial API services severely hinder academic research and industrial adoption; moreover, existing tools lack modular, extensible analytical frameworks. To address these challenges, we propose the first open-source on-chain data integration framework, which directly parses RPC responses and ingests real-time data streams to enable low-cost, high-fidelity, multi-chain data collection and unified management. The framework features a lightweight API interface and a layered backend architecture, supporting plug-and-play module extension and significantly lowering integration barriers. Experimental evaluation demonstrates over 80% reduction in data acquisition cost compared to mainstream RPC providers. All source code and benchmark datasets are publicly released, establishing a cost-effective, systematic, and accessible infrastructure for blockchain data analytics.
📝 Abstract
Blockchain technologies are rapidly transforming both academia and industry. However, large-scale blockchain data collection remains prohibitively expensive, as many RPC providers only offer enhanced APIs with high pricing tiers that are unsuitable for budget-constrained research or industrial-scale applications, which has significantly slowed down academic studies and product development. Moreover, there is a clear lack of a systematic framework that allows flexible integration of new modules for analyzing on-chain data.
To address these challenges, we introduce LinkXplore, the first open framework for collecting and managing on-chain data. LinkXplore enables users to bypass costly blockchain data providers by directly analyzing raw data from RPC queries or streams, thereby offering high-quality blockchain data at a fraction of the cost. Through a simple API and backend processing logic, any type of chain data can be integrated into the framework. This makes it a practical alternative for both researchers and developers with limited budgets. Code and dataset used in this project are publicly available at https://github.com/Linkis-Project/LinkXplore