DBpedia SPARQL Benchmark – Performance Assessment with Real Queries on Real Data

  • Mohamed Morsey
  • Jens Lehmann
  • Sören Auer
  • Axel-Cyrille Ngonga Ngomo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7031)


Triple stores are the backbone of increasingly many Data Web applications. It is thus evident that the performance of those stores is mission critical for individual projects as well as for data integration on the Data Web in general. Consequently, it is of central importance during the implementation of any of these applications to have a clear picture of the weaknesses and strengths of current triple store implementations. In this paper, we propose a generic SPARQL benchmark creation procedure, which we apply to the DBpedia knowledge base. Previous approaches often compared relational and triple stores and, thus, settled on measuring performance against a relational database which had been converted to RDF by using SQL-like queries. In contrast to those approaches, our benchmark is based on queries that were actually issued by humans and applications against existing RDF data not resembling a relational schema. Our generic procedure for benchmark creation is based on query-log mining, clustering and SPARQL feature analysis. We argue that a pure SPARQL benchmark is more useful to compare existing triple stores and provide results for the popular triple store implementations Virtuoso, Sesame, Jena-TDB, and BigOWLIM. The subsequent comparison of our results with other benchmark results indicates that the performance of triple stores is by far less homogeneous than suggested by previous benchmarks.


Resource Description Framework Dataset Size SPARQL Query Triple Pattern Resource Description Framework Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Mohamed Morsey
    • 1
  • Jens Lehmann
    • 1
  • Sören Auer
    • 1
  • Axel-Cyrille Ngonga Ngomo
    • 1
  1. 1.Department of Computer ScienceUniversity of LeipzigLeipzigGermany

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