Querying Wikidata: Comparing SPARQL, relational and graph databases

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Abstract

In this paper, we experimentally compare the efficiency of various database engines for the purposes of querying the Wikidata knowledge-base, which can be conceptualised as a directed edge-labelled graph where edges can be annotated with meta-information called qualifiers. We take two popular SPARQL databases (Virtuoso, Blazegraph), a popular relational database (PostgreSQL), and a popular graph database (Neo4J) for comparison and discuss various options as to how Wikidata can be represented in the models of each engine. We design a set of experiments to test the relative query performance of these representations in the context of their respective engines. We first execute a large set of atomic lookups to establish a baseline performance for each test setting, and subsequently perform experiments on instances of more complex graph patterns based on real-world examples. We conclude with a summary of the strengths and limitations of the engines observed.

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APA

Hernández, D., Hogan, A., Riveros, C., Rojas, C., & Zerega, E. (2016). Querying Wikidata: Comparing SPARQL, relational and graph databases. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9982 LNCS, pp. 88–103). Springer Verlag. https://doi.org/10.1007/978-3-319-46547-0_10

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