StarBench: Benchmarking RDF-star Triplestores

Ghadeer Abuoda*, Christian Aebeloe, Daniele Dell'Aglio, Arthur Keen, Katja Hose

*Corresponding author for this work

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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Abstract

RDF-star has rapidly gained popularity as a way to annotate RDF statements while avoiding the disadvantages of reification. Hence, a number of triplestores supporting this new standard have become available.
Yet, it is difficult to assess the performance of these systems and to which degree they support RDF-star
and the corresponding SPARQL-star query language. Hence, in this paper, we propose StarBench, a
benchmark for testing SPARQL-star support and runtime performance. We ran StarBench on a number
of state-of-the-art triplestores with RDF-star and SPARQL-star support and share our findings. Based on
these findings, we highlight existing challenges and research opportunities.
Original languageEnglish
Title of host publicationJoint Proceedings of the QuWeDa and MEPDaW 2023: 7th Workshop on Storing, Querying and Benchmarking Knowledge Graphs and 9th Workshop on Managing the Evolution and Preservation of the Data Web co-located with 22nd International Semantic Web Conference (ISWC 2023)
Number of pages16
PublisherCEUR Workshop Proceedings
Publication date2023
Publication statusPublished - 2023
EventQuWeDa 2023: 7th Workshop on Storing, Querying and Benchmarking Knowledge Graphs - Athen, Greece
Duration: 6 Nov 202310 Nov 2023

Conference

ConferenceQuWeDa 2023: 7th Workshop on Storing, Querying and Benchmarking Knowledge Graphs
Country/TerritoryGreece
CityAthen
Period06/11/202310/11/2023
SeriesCEUR Workshop Proceedings
Volume3565
ISSN1613-0073

Keywords

  • RDF
  • RDF-star
  • Property graphs

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