QLever (pronounced , as in "clever") 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.
A 2023 study compared QLever with Virtuoso, Blazegraph, GraphDB, Stardog, Apache Jena, and Oxigraph. As part of the EU Next Generation Internet (NGI) Search programme, QLever achieved full SPARQL 1.1 compliance in June 2025, including support for SPARQL UPDATE, enabling read/write operations.
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.
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.