An Evaluation of RDF Storage Systems for Large Data Applications

Authors:
Baolin Liu;Bo Hu
Affiliations:
Tsinghua University, Beijing 100084, P.R.China;Tsinghua University, Beijing 100084, P.R.China
Venue:
SKG '05 Proceedings of the First International Conference on Semantics, Knowledge and Grid
Year:
2005

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Abstract

In this paper, evaluation on 7 RDF storage systems with respect to the large data applications is presented. By using the toolkit LUBM-R, 4 different scales of RDF datasets to proceed with benchmark are gotten. The target systems which are evaluated includes two storage systems based on memory (Sesame-Memory and Jena-Memory), two persistent storage systems with RDBMS underlying (Sesame-DB and Jena-DB), and three native RDF approach systems (Sesame- Native, Kowari and YARS). We described how we have performed the evaluation and discussed several issues about the results. We also introduced a combined metric to measure the overall performance of a RDF storage system. And the results show several issues about current RDF storage system.