Abouda, G., Aebeloe, C., Dell’Aglio, D., Keen, A., & Hose, K. (2023). StarBench: Benchmarking RDF-star Triplestores. In M. U. Saleem, A.-C. Ngonga Ngomo, D. Graux, F. Orlandi, E. Niazmand, G. Ydler, & M.-E. Vidal (Eds.), Joint 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 (QuWeDa-MEPDaW 2023) (pp. 34–49). CEUR-WS.org. https://doi.org/10.34726/5399
E192-02 - Forschungsbereich Databases and Artificial Intelligence
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Erschienen in:
Joint 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 (QuWeDa-MEPDaW 2023)
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Band:
3565
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Datum (veröffentlicht):
27-Nov-2023
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Veranstaltungsname:
7th Workshop on Storing, Querying and Benchmarking Knowledge Graphs and 9th Workshop on Managing the Evolution and Preservation of the Data Web (QuWeDa-MEPDaW 2023)
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.
CC BY 4.0
