qlever

name	qlever
description	Query, configure, and optimize QLever—the high-performance open-source RDF triplestore. Covers SPARQL queries, GeoSPARQL, text search, CLI operations, and public endpoints. Informed by Kurt Cagle's semantic web expertise.
allowed-tools	Read, Write, Edit, Grep, Glob, Bash, WebFetch

QLever Skill

Master QLever, the high-performance open-source RDF graph database developed by Hannah Bast's team at the University of Freiburg. QLever handles hundreds of billions of triples on commodity hardware, implements full SPARQL 1.1, and offers unique features for text search, GeoSPARQL, and context-sensitive autocompletion.

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Core Philosophy (Cagle's Perspective)

"QLever represents the next generation of knowledge graph infrastructure—where SPARQL meets scale without compromise."

Why QLever Matters:

1. Scale without sacrifice: Handle Wikidata's 18+ billion triples on a single machine with sub-second query times
2. SPARQL 1.1 complete: Full standard compliance including federated queries, named graphs, and SPARQL Update
3. Beyond plain SPARQL: Integrated text search (ql:contains-word, ql:contains-entity) and GeoSPARQL support
4. Developer experience: Context-sensitive autocompletion makes query writing accessible to non-experts
5. Open source excellence: Apache 2.0 licensed, active development, strong academic foundation

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Guide Router

Load only ONE guide per request. Match user intent to the most specific keywords:

User Intent	Load Guide	Content
Installation, CLI, Qleverfile setup	02-INSTALLATION-CLI.md	pip install, docker, configuration
Basic SPARQL queries, SELECT, CONSTRUCT	03-QUERY-PATTERNS.md	Query forms, patterns, examples
Text search, ql:contains-word, full-text	04-TEXT-SEARCH.md	SPARQL+Text predicates
GeoSPARQL, spatial queries, OSM data	05-GEOSPARQL.md	ogc:sfContains, sfIntersects
Federated queries, SERVICE, Wikidata	06-FEDERATION.md	Multi-endpoint queries
Public endpoints, demos, datasets	07-PUBLIC-ENDPOINTS.md	Wikidata, OSM, UniProt
Performance, optimization, benchmarks	08-PERFORMANCE.md	Tuning, comparisons
HTTP API, JSON results, curl	09-HTTP-API.md	REST endpoints, formats
SPARQL Update, INSERT, DELETE	10-UPDATES.md	Data modification

Default behavior: If intent is unclear, start with this entry point's quick reference.

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QLever Quick Reference

What is QLever?

QLever (pronounced "clever") is:

• Graph database: Implements RDF and SPARQL standards
• High-performance: 5-10x faster than Blazegraph/Virtuoso on most queries
• Scalable: Handles 100+ billion triples, tested to 1 trillion
• Feature-rich: Text search, GeoSPARQL, autocompletion, live query analysis
• Open source: Apache 2.0 license, active development

Key Capabilities

Feature	Description
SPARQL 1.1	Full compliance including UPDATE, federated queries, named graphs
Text Search	ql:contains-word, ql:contains-entity for combined semantic+text queries
GeoSPARQL	ogc:sfContains, ogc:sfIntersects, distance calculations
Autocompletion	Context-sensitive suggestions for entities, predicates, objects
Visualization	Map rendering of millions of geometric objects
Query Analysis	Live execution plans and performance insights

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Installation

Quick Start with pip

# Install qlever CLI (recommended: use pipx or uv)
pip install qlever
# or
pipx install qlever
# or
uv tool install qlever

# Get a preconfigured dataset
qlever setup-config olympics
qlever get-data
qlever index
qlever start

# Test with a query
qlever query "SELECT * WHERE { ?s ?p ?o } LIMIT 10"

# Launch the web UI
qlever ui

Available Configurations

# List available preconfigured datasets
qlever setup-config --list

# Popular options:
qlever setup-config wikidata      # Complete Wikidata (18B+ triples)
qlever setup-config osm-planet    # OpenStreetMap (40B+ triples)
qlever setup-config olympics      # Small demo (2M triples)
qlever setup-config dblp          # Computer science bibliography
qlever setup-config uniprot       # Protein database

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The Qleverfile

All QLever operations are controlled by a single configuration file called Qleverfile:

# Example Qleverfile for custom dataset
[data]
NAME = my-knowledge-graph
GET_DATA_CMD = curl -L -o data.ttl https://example.org/data.ttl
FORMAT = turtle

[index]
INPUT_FILES = data.ttl
SETTINGS_JSON = {"prefixes": {"": "http://example.org/"}}

[server]
PORT = 7001
MEMORY_FOR_QUERIES = 10G
CACHE_MAX_SIZE = 5G

[ui]
UI_PORT = 7000

CLI Commands

Command	Description
qlever setup-config <name>	Fetch preconfigured Qleverfile
qlever get-data	Download dataset
qlever index	Build index structures
qlever start	Start SPARQL server
qlever stop	Stop server
qlever query "<sparql>"	Execute query
qlever ui	Launch web interface
qlever status	Show server status
qlever log	View server logs
qlever --show	Preview command without executing

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SPARQL Query Examples

Basic Queries

# Find all types of entities
SELECT ?type (COUNT(?s) AS ?count)
WHERE { ?s a ?type }
GROUP BY ?type
ORDER BY DESC(?count)
LIMIT 20

# Get entity with all properties
SELECT ?predicate ?object
WHERE { <http://example.org/entity1> ?predicate ?object }

# Find entities by label
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?entity ?label
WHERE {
  ?entity rdfs:label ?label .
  FILTER (CONTAINS(LCASE(STR(?label)), "example"))
}
LIMIT 100

QLever Text Search

# Find entities mentioned with specific words
PREFIX ql: <http://qlever.cs.uni-freiburg.de/builtin/>

SELECT ?entity ?text (COUNT(?text) AS ?mentions)
WHERE {
  ?text ql:contains-entity ?entity .
  ?text ql:contains-word "artificial intelligence" .
}
GROUP BY ?entity ?text
ORDER BY DESC(?mentions)
LIMIT 20

# Wildcard text search
SELECT ?entity ?text
WHERE {
  ?text ql:contains-entity ?entity .
  ?text ql:contains-word "machine learn*" .  # Matches learning, learns, etc.
}

GeoSPARQL Queries

# Find all elements within a geographic region (e.g., France)
PREFIX ogc: <http://www.opengis.net/rdf#>
PREFIX osmrel: <https://www.openstreetmap.org/relation/>
PREFIX osmkey: <https://www.openstreetmap.org/wiki/Key:>

SELECT ?element ?name
WHERE {
  osmrel:2202162 ogc:sfContains ?element .  # France relation ID
  ?element osmkey:railway "station" ;
           osmkey:name ?name .
}
LIMIT 100

# Calculate distance between points
PREFIX geof: <http://www.opengis.net/def/function/geosparql/>

SELECT ?place1 ?place2 ?distance
WHERE {
  ?place1 geo:hasGeometry/geo:asWKT ?geom1 .
  ?place2 geo:hasGeometry/geo:asWKT ?geom2 .
  BIND(geof:distance(?geom1, ?geom2, <http://www.opengis.net/def/uom/OGC/1.0/kilometre>) AS ?distance)
  FILTER(?distance < 10)
}

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HTTP API

Query Endpoint

# Basic query (TSV output)
curl -s "https://qlever.dev/api/wikidata" \
  -H "Accept: text/tab-separated-values" \
  -H "Content-Type: application/sparql-query" \
  --data "SELECT * WHERE { ?s ?p ?o } LIMIT 10"

# JSON output (SPARQL Results JSON)
curl -s "https://qlever.dev/api/wikidata" \
  -H "Accept: application/sparql-results+json" \
  -H "Content-Type: application/sparql-query" \
  --data "SELECT ?s ?p ?o WHERE { ?s ?p ?o } LIMIT 10"

# QLever custom JSON format
curl -s "https://qlever.dev/api/wikidata" \
  -H "Accept: application/qlever-results+json" \
  -H "Content-Type: application/sparql-query" \
  --data "SELECT ?s ?p ?o WHERE { ?s ?p ?o } LIMIT 10"

Supported Media Types

Accept Header	Format
text/csv	CSV
text/tab-separated-values	TSV
application/sparql-results+json	W3C SPARQL JSON
application/qlever-results+json	QLever custom JSON
application/sparql-results+xml	SPARQL XML

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Public Endpoints

QLever Demo Instances

Dataset	Endpoint	Triples
Wikidata	https://qlever.dev/api/wikidata	18B+
OpenStreetMap	https://qlever.dev/api/osm-planet	40B+
UniProt	https://qlever.dev/api/uniprot	100B+
PubChem	https://qlever.dev/api/pubchem	150B+
DBLP	https://sparql.dblp.org/sparql	390M
DBpedia	https://qlever.dev/api/dbpedia	1B+
Freebase	https://qlever.dev/api/freebase	3B+

Accessing Demo UI

Visit https://qlever.dev/ for interactive query interfaces with:

• Context-sensitive autocompletion
• Example queries (70+ per dataset)
• Map visualization for geographic data
• Result download (CSV/TSV)

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Performance Benchmarks

QLever vs Other Engines (DBLP Dataset, 390M Triples)

Engine	Index Time	Index Size	Avg Query Time
QLever	231s	8 GB	0.7s
Virtuoso	561s	13 GB	2.2s
GraphDB	1,066s	28 GB	16s
Blazegraph	6,326s	67 GB	4.3s
Apache Jena	2,392s	42 GB	varies

Wikidata Benchmark (298 queries)

Metric	QLever	Official WDQS	Virtuoso
Success Rate	98%	79%	89%
Queries <1s	78%	36%	54%
Avg Time	1.38s	6.98s	4.11s
Median Time	0.24s	2.47s	0.74s

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QLeverize (Enterprise)

QLeverize provides commercial support from the QLever team:

Tier	Features
Community	Free, open source, GitHub Issues support
Standard	Priority support, private issue tracking, QA binaries
Enterprise	24/7 support, SLAs, priority features, managed hosting

Services include:

• Enterprise consulting and query optimization
• Managed cloud deployments (Azure/AWS)
• Embedded/edge solutions for automotive, medical, IoT
• Pre-loaded datasets (Wikidata, UniProt, PubChem, OSM)

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Common Patterns

Wikidata Query

PREFIX wd: <http://www.wikidata.org/entity/>
PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>

# Find all universities with founding date
SELECT ?university ?name ?founded
WHERE {
  ?university wdt:P31 wd:Q3918 ;      # instance of university
              rdfs:label ?name ;
              wdt:P571 ?founded .      # inception date
  FILTER (LANG(?name) = "en")
}
ORDER BY ?founded
LIMIT 100

OpenStreetMap Query

PREFIX osmkey: <https://www.openstreetmap.org/wiki/Key:>
PREFIX osm2rdf: <https://osm2rdf.cs.uni-freiburg.de/rdf#>
PREFIX geo: <http://www.opengis.net/ont/geosparql#>

# Find all cafes with their locations
SELECT ?cafe ?name ?geometry
WHERE {
  ?cafe osmkey:amenity "cafe" ;
        osmkey:name ?name ;
        geo:hasGeometry/geo:asWKT ?geometry .
}
LIMIT 100

Federated Query

PREFIX wdt: <http://www.wikidata.org/prop/direct/>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>

SELECT ?item ?itemLabel ?osmElement
WHERE {
  # Local OSM data
  ?osmElement osmkey:wikidata ?wikidataId .

  # Federated query to Wikidata
  SERVICE <https://query.wikidata.org/sparql> {
    ?item wdt:P31 wd:Q515 ;       # instance of city
          rdfs:label ?itemLabel .
    FILTER (LANG(?itemLabel) = "en")
  }
  FILTER (STR(?item) = ?wikidataId)
}
LIMIT 50

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Troubleshooting

Common Issues

Issue	Solution
Index fails	Check disk space, increase memory in Qleverfile
Query timeout	Add LIMIT, simplify patterns, check index
Port in use	Change PORT in Qleverfile or qlever stop first
Docker permission denied	Run with sudo or add user to docker group

Debugging

# Show what command would execute
qlever index --show

# Check server status
qlever status

# View logs
qlever log

# Test with simple query
qlever query "SELECT (COUNT(*) AS ?count) WHERE { ?s ?p ?o }"

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Resources

Official

• Documentation: https://docs.qlever.dev/
• GitHub: https://github.com/ad-freiburg/qlever
• Public Demos: https://qlever.dev/
• PyPI: https://pypi.org/project/qlever/
• QLeverize: https://www.qleverize.com/

Academic

• QLever: A Query Engine for Efficient SPARQL+Text Search (CIKM 2017)
• Efficient SPARQL Autocompletion via SPARQL (CIKM 2022)
• Sparqloscope Benchmark (ISWC 2025)

Community

• Hannah Bast's Research Group
• QLever Wiki (OpenStreetMap)
• DBLP SPARQL Service

Kurt Cagle's Work

• The Ontologist - Substack newsletter
• The Cagle Report - Enterprise data and AI
• Why SPARQL Is Poised To Set the World on Fire - LinkedIn