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| Title | Querying Wikidata: Comparing SPARQL, Relational and Graph Databases |
| Authors | Daniel Hernández, Aidan Hogan, Cristian Riveros, Carlos Rojas, Enzo Zerega |
| Publication date | 2016 |
| 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. |
| Pages | 88-103 |
| Conference name | International Semantic Web Conference |
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