Improving the Performance of Semantic Web Applications with SPARQL Query Caching

  • Michael Martin
  • Jörg Unbehauen
  • Sören Auer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6089)


The performance of triple stores is one of the major obstacles for the deployment of semantic technologies in many usage scenarios. In particular, Semantic Web applications, which use triple stores as persistence backends, trade performance for the advantage of flexibility with regard to information structuring. In order to get closer to the performance of relational database-backed Web applications, we developed an approach for improving the performance of triple stores by caching query results and even complete application objects. The selective invalidation of cache objects, following updates of the underlying knowledge bases, is based on analysing the graph patterns of cached SPARQL queries in order to obtain information about what kind of updates will change the query result. We evaluated our approach by extending the BSBM triple store benchmark with an update dimension as well as in typical Semantic Web application scenarios.


Query Result Graph Pattern SPARQL Query Triple Pattern Cache Proxy 
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 2010

Authors and Affiliations

  • Michael Martin
    • 1
  • Jörg Unbehauen
    • 1
  • Sören Auer
    • 1
  1. 1.Institut für InformatikUniversität LeipzigLeipzigGermany

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