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QLever
Freiburg, Germany
What it is
QLever is a free, open-source graph database for loading and querying large RDF datasets. It implements SPARQL 1.1, with federated queries, named graphs, updates, and the Graph Store HTTP Protocol. The project says it can handle more than a trillion triples on one commodity machine. It also provides text search across knowledge bases, context-sensitive SPARQL autocomplete, live query analysis, and spatial queries with interactive maps of geometric objects. QLever can run embedded in C++ code without a client-server setup. Example datasets include Wikidata, Wikimedia Commons, OpenStreetMap, UniProt, PubChem, and DBLP. Deployment is self-hosted, with packages for Debian, Ubuntu and its derivatives, and macOS, plus Docker and Podman images. The Homebrew package is for ARM64 Apple Silicon, not Intel Macs. Windows use requires Docker in a virtual machine and may carry significant performance and RAM costs; binary releases are in progress. A web interface and backend API provide query access, including GET and POST examples using curl. QLever is licensed under Apache 2.0.
For and against
For
- Free and open source under Apache 2.0.
- Implements SPARQL 1.1, including federated queries.
- Includes text search and spatial map visualization.
- Can run embedded in C++ code.
- Packages and container images are available.
Against
- Windows use requires Docker in a virtual machine.
- Homebrew package does not support Intel Macs.
- Deployment is self-hosted.
The verdict
QLever brings SPARQL, text search, and spatial querying together for RDF workloads, with an embedded option as well. Check the platform constraints before choosing how to deploy it.
Who it suits
QLever suits developers and teams working with large RDF datasets who need SPARQL querying, text search, or spatial features. Its embedded C++ option may suit projects that want a database without a separate client-server setup.
Plans and prices
QLever
Open-source software · Apache 2.0 license
Read 5 Oct 2026 · github.com
On the record
- Dataset examples
- The project lists demos for Wikidata, Wikimedia Commons, OpenStreetMap, UniProt, PubChem, and DBLP.github.com · read 5 Oct 2026
- Embedded use
- QLever can run as an embedded database inside C++ code without a client-server setup.github.com · read 5 Oct 2026
- Installation
- Official packages are available for Debian, Ubuntu, Ubuntu-derived distributions, and macOS; Docker and Podman images are also available.docs.qlever.dev · read 5 Oct 2026
- Integrations
- The QLever UI exposes backend API URLs and offers query access via GET and POST examples using curl.qlever.dev · read 5 Oct 2026
- macOS limit
- The official Homebrew package supports ARM64 Apple Silicon Macs; Intel Macs are not supported by that package.docs.qlever.dev · read 5 Oct 2026
- Query assistance
- QLever provides context-sensitive autocompletion for SPARQL queries and live query analysis.github.com · read 5 Oct 2026
- Scale
- The project says QLever scales to more than a trillion triples on a single commodity machine.github.com · read 5 Oct 2026
- Security and compliance
- The opened maker pages identify the Apache 2.0 license but do not state a security certification or compliance program.github.com · read 5 Oct 2026
- SPARQL support
- QLever implements SPARQL 1.1, including federated queries, named graphs, the Graph Store HTTP Protocol, and updates.github.com · read 5 Oct 2026
- Spatial features
- QLever supports efficient spatial queries and interactive map visualization of large numbers of geometric objects.github.com · read 5 Oct 2026
- Support
- For bugs or missing features, the project asks users to search existing GitHub issues or open an issue or discussion.github.com · read 5 Oct 2026
- Text search
- QLever includes text search over knowledge bases.github.com · read 5 Oct 2026
- What it does
- QLever is a graph database implementing RDF and SPARQL for loading and querying large datasets.github.com · read 5 Oct 2026
- Windows limit
- The documentation says Windows use runs Docker inside a virtual machine and may incur significant performance and RAM costs; binary releases are in progress.docs.qlever.dev · read 5 Oct 2026
