BigChain: Consolidating Blockchain Client for Scalable Analysis

Abstract

Blockchains have been widely adopted to track critical data in complicated applications recently, thus it is necessary to provide efficient infrastructure to analyze large-scale chain data. However, the current blockchain clients are mostly designed for a single node with limited storage space and the separated data analysis systems are not suitable for huge chains due to redundant data transformation and scalability. To address these challenges, we propose BigChain, a distributed blockchain client with built-in bigdata processing capability. BigChain is designed on top of HBase by mapping blockchain entities to HBase’s KV storage to guarantee the rapid growth of on-chain data. By integrating the MapReduce framework, BigChain could leverage the Hadoop big data ecosystem directly to analyze blockchain data in a scalable manner. Additionally, an indexing service is devised accordingly to speed up BigChain. Finally, comprehensive experiments were conducted against Ethereum, and the results indicate that BigChain can outperform typical clients by 10 times in terms of comprehensive scenarios.