Abstract
This paper presents a comparison of performance of various triple-store technologies currently in either production release or beta test. Our comparison of triple-store technologies is biased toward a deployment scenario where the triple-store needs to load data and respond to queries over a very large knowledge base (on the order of hundreds of millions of triples.) The comparisons in this paper are based on the Lehigh University Benchmark (LUBM) software tools. We used the LUBM university ontology, datasets, and standard queries to perform our comparisons. We find that over our test regimen, the triple-stores based on the DAML DB and BigOWLIM technologies exhibit the best performance among the triple-stores tested.
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Rohloff, K., Dean, M., Emmons, I., Ryder, D., Sumner, J. (2007). An Evaluation of Triple-Store Technologies for Large Data Stores. In: Meersman, R., Tari, Z., Herrero, P. (eds) On the Move to Meaningful Internet Systems 2007: OTM 2007 Workshops. OTM 2007. Lecture Notes in Computer Science, vol 4806. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76890-6_38
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DOI: https://doi.org/10.1007/978-3-540-76890-6_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76889-0
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