QLever


QLever is an open-source triplestore and graph database developed by a team at the University of Freiburg led by Hannah Bast. QLever performs high-performance queries of semantic Web knowledge bases, including full-text search within text corpuses. A specialized user interface for QLever predictively autocompletes SPARQL queries.

History

A 2023 study compared QLever with Virtuoso, Blazegraph, GraphDB, Stardog, Apache Jena, and Oxigraph. The study investigated a QLever version from 2021, concluding that it achieved fast execution of successful queries but offered limited support for complex SPARQL constructs.

Contents

The official QLever instance provides API endpoints for querying the following datasets:
For OpenStreetMap and OpenHistoricalMap data, the QLever engine supports a limited subset of GeoSPARQL functions, supplemented by a precomputed subset of GeoSPARQL relationships stored as dedicated triples.

Adoption

Besides the official instance, the QLever engine also powers the official SPARQL endpoint of DBLP. QLever is one of the candidates to replace Blazegraph as the triplestore for the Wikidata [Query Service].