Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/15569
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dc.contributor.authorJovanovik, Milosen_US
dc.contributor.authorSpasić, Mirkoen_US
dc.date.accessioned2021-12-02T11:24:12Z-
dc.date.available2021-12-02T11:24:12Z-
dc.date.issued2018-10-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/15569-
dc.description.abstractFollowing the success of Virtuoso at last year’s Mighty Storage Challenge - MOCHA 2017, we decided to participate once again and test the latest Virtuoso version against the new tasks which comprise the MOCHA 2018 challenge. The aim of the challenge is to test the performance of solutions for SPARQL processing in aspects relevant for modern applications: ingesting data, answering queries on large datasets and serving as backend for applications driven by Linked Data. The challenge tests the systems against data derived from real applications and with realistic loads, with an emphasis on dealing with changing data in the form of streams or updates. Virtuoso, by OpenLink Software, is a modern enterprise-grade solution for data access, integration, and relational database management, which provides a scalable RDF Quad Store. In this paper, we present the final challenge results from MOCHA 2018 for Virtuoso v8.0, compared to the other participating systems. Based on these results, Virtuoso v8.0 was declared as the overall winner of MOCHA 2018.en_US
dc.language.isoenen_US
dc.publisherSpringer International Publishingen_US
dc.subjectVirtuosoen_US
dc.subjectMighty Storage Challengeen_US
dc.subjectMOCHAen_US
dc.subjectBenchmarkingen_US
dc.subjectData Storageen_US
dc.subjectLinked Dataen_US
dc.subjectRDFen_US
dc.subjectSPARQLen_US
dc.titleBenchmarking Virtuoso 8 at the Mighty Storage Challenge 2018: Challenge Resultsen_US
dc.typeBook chapteren_US
dc.typeProceeding articleen_US
dc.relation.conferenceSemantic Web Challengesen_US
dc.relation.conferenceESWC 2018en_US
dc.identifier.doi10.1007/978-3-030-00072-1_3-
dc.identifier.urlhttp://link.springer.com/content/pdf/10.1007/978-3-030-00072-1_3-
item.grantfulltextnone-
item.fulltextNo Fulltext-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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