Datachain: A query framework for blockchains

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publication11th International Conference on Management of Digital EcoSystems, MEDES 2019
PublisherAssociation for Computing Machinery, Inc
Pages134-141
Number of pages8
ISBN (Electronic)9781450362382
DOIs
Publication statusPublished - 12 Nov 2019
Event11th International Conference on Management of Digital EcoSystems, MEDES 2019 - Limassol, Cyprus
Duration: 12 Nov 201914 Nov 2019

Publication series

Name11th International Conference on Management of Digital EcoSystems, MEDES 2019

Conference

Conference11th International Conference on Management of Digital EcoSystems, MEDES 2019
Country/TerritoryCyprus
CityLimassol
Period12/11/1914/11/19

Keywords

  • Analytics
  • Blockchain
  • Data Mining

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