TY - GEN
T1 - Datachain
T2 - 11th International Conference on Management of Digital EcoSystems, MEDES 2019
AU - Trihinas, Demetris
N1 - Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/11/12
Y1 - 2019/11/12
N2 - 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.
AB - 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.
KW - Analytics
KW - Blockchain
KW - Data Mining
UR - http://www.scopus.com/inward/record.url?scp=85078695331&partnerID=8YFLogxK
U2 - 10.1145/3297662.3365796
DO - 10.1145/3297662.3365796
M3 - Conference contribution
AN - SCOPUS:85078695331
T3 - 11th International Conference on Management of Digital EcoSystems, MEDES 2019
SP - 134
EP - 141
BT - 11th International Conference on Management of Digital EcoSystems, MEDES 2019
PB - Association for Computing Machinery, Inc
Y2 - 12 November 2019 through 14 November 2019
ER -