Interoperable data extraction and analytics queries over blockchains

Abstract

The explosion of interests by diverse organisations for deploying their services on blockchains to exploit decentralize transaction governance and advanced cryptographic protocols, is fostering the emergence of new challenges for distributed ledger technologies (DLTs). The next generation of blockchain services are now extending well beyond cryptocurrencies, accumulating and storing vast amounts of data. Therefore, the need to efficiently extract data over blockchains and subsequently foster data analytics, is more evident than ever. However, despite the wide public interest and the release of several frameworks, efficiently accessing and processing data from blockchains still imposes significant challenges. This article, first, introduces the key limitations faced by organisations in need for efficiently accessing and managing data over DLTs. Afterwards, it introduces Datachain, a lightweight, flexible and interoperable framework deliberately designed to ease the extraction of data hosted on DLTs. Through high-level query abstractions, users connect to underlying blockchains, perform data requests, extract transactions, manage data assets and derive high-level analytic insights. Most importantly, due to the inherent interoperable nature of Datachain, queries and analytic jobs are reusable and can be executed without alterations on different underlying blockchains. To illustrate the wide applicability of Datachain, we present a realistic use-case on top of Hyperledger and BigchainDB.