Fueled by the wide societal interest for decentralized services, blockchain has emerged into a highly desired paradigm extending well beyond financial transactions. The next generation of blockchain services are now storing more and more data on distributed ledgers. Therefore, the need to perform analytic queries over blockchains is more evident than ever. However, despite the wide public interest and the release of several frameworks, efficiently accessing and processing data from blockchains is challenging. This paper introduces Datachain, a lightweight, flexible and interoperable framework deliberately designed to ease the extraction of data hosted on distributed ledgers. 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.
|Title of host publication||MEDES '19: Proceedings of the 11th International Conference on Management of Digital EcoSystems|
|Publisher||Association for Computing Machinery (ACM)|
|Number of pages||8|
|Publication status||Published - Nov 2019|