Chapter

The Semantic Web – ISWC 2013

Volume 8219 of the series Lecture Notes in Computer Science pp 310-325

NoSQL Databases for RDF: An Empirical Evaluation

  • Philippe Cudré-MaurouxAffiliated withCarnegie Mellon UniversityUniversity of Fribourg
  • , Iliya EnchevAffiliated withCarnegie Mellon UniversityUniversity of Fribourg
  • , Sever FundatureanuAffiliated withCarnegie Mellon UniversityVU University Amsterdam
  • , Paul GrothAffiliated withCarnegie Mellon UniversityVU University Amsterdam
  • , Albert HaqueAffiliated withCarnegie Mellon UniversityUniversity of Texas at Austin
  • , Andreas HarthAffiliated withCarnegie Mellon UniversityKarlsruhe Institute of Technology
  • , Felix Leif KeppmannAffiliated withCarnegie Mellon UniversityKarlsruhe Institute of Technology
  • , Daniel MirankerAffiliated withCarnegie Mellon UniversityUniversity of Texas at Austin
  • , Juan F. SequedaAffiliated withCarnegie Mellon UniversityUniversity of Texas at Austin
    • , Marcin WylotAffiliated withCarnegie Mellon UniversityUniversity of Fribourg

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Abstract

Processing large volumes of RDF data requires sophisticated tools. In recent years, much effort was spent on optimizing native RDF stores and on repurposing relational query engines for large-scale RDF processing. Concurrently, a number of new data management systems—regrouped under the NoSQL (for “not only SQL”) umbrella—rapidly rose to prominence and represent today a popular alternative to classical databases. Though NoSQL systems are increasingly used to manage RDF data, it is still difficult to grasp their key advantages and drawbacks in this context. This work is, to the best of our knowledge, the first systematic attempt at characterizing and comparing NoSQL stores for RDF processing. In the following, we describe four different NoSQL stores and compare their key characteristics when running standard RDF benchmarks on a popular cloud infrastructure using both single-machine and distributed deployments.