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Evaluation of a Representative Selection of SPARQL Query Engines Using Wikidata

Abstract

In this paper, we present an evaluation of the performance of five representative RDF triplestores, including GraphDB, Jena Fuseki, Neptune, RDFox, and Stardog, and one experimental SPARQL query engine, QLever. We compare importing time, loading time, and exporting time using a complete version of the knowledge graph Wikidata, and we also evaluate query performances using 328 queries defined by Wikidata users. To put this evaluation into context with respect to previous evaluations, we also analyze the query performances of these systems using a prominent synthetic benchmark: SP2Bench. We observed that most of the systems we considered for the evaluation were able to complete the execution of almost all the queries defined by Wikidata users before the timeout we established. We noticed, however, that the time needed by most systems to import and export Wikidata might be longer than required in some industrial and academic projects, where information is represented, enriched, and stored using different representation means.
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Category

Academic chapter

Language

English

Affiliation

  • SINTEF Digital / Sustainable Communication Technologies

Year

2023

Publisher

Springer

Book

The Semantic Web: 20th International Conference, ESWC 2023, Hersonissos, Crete, Greece, May 28–June 1, 2023, Proceedings

ISBN

9783031334559

Page(s)

679 - 696

View this publication at Norwegian Research Information Repository