colliery-io/graphqlite
colliery-io/graphqlite has 527 GitHub stars and 33 forks. Star changes are not measured yet. Last checked 2026-11-10 04:24 UTC. Last push 2026-11-09.
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A SQLite extension that adds graph database capabilities with Cypher query language support and built-in graph algorithms.
What you can do
- Cypher queries — MATCH, CREATE, MERGE, SET, DELETE, WITH, UNWIND, RETURN
- Graph algorithms — PageRank, Louvain, Dijkstra, BFS/DFS, connected components, and more
- Zero configuration — Works with any SQLite database, no server required
- Multiple bindings — Python, Rust, and raw SQL interfaces
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Variations nettes sur des périodes qui se chevauchent, pas des totaux quotidiens. Les mesures absentes restent vides. Les étoiles indiquent l’intérêt, pas la qualité.
README.md
OriginalGraphQLite
An SQLite extension that adds graph database capabilities using the Cypher query language.
Store and query graph data directly in SQLite—combining the simplicity of a single-file, zero-config embedded database with Cypher's expressive power for modeling relationships.
Installation
brew install graphqlite # macOS/Linux (Homebrew)
pip install graphqlite # Python
cargo add graphqlite # Rust
Quick Start
from graphqlite import Graph
g = Graph(":memory:")
g.upsert_node("alice", {"name": "Alice", "age": 30}, label="Person")
g.upsert_node("bob", {"name": "Bob", "age": 25}, label="Person")
g.upsert_edge("alice", "bob", {"since": 2020}, rel_type="KNOWS")
# Query with Cypher
results = g.query("MATCH (a:Person)-[:KNOWS]->(b) RETURN a.name, b.name")
# Built-in graph algorithms
g.pagerank()
g.louvain()
g.dijkstra("alice", "bob")
Features
- Cypher queries — MATCH, CREATE, MERGE, SET, DELETE, WITH, UNWIND, RETURN
- Graph algorithms — PageRank, Louvain, Dijkstra, BFS/DFS, connected components, and more
- Zero configuration — Works with any SQLite database, no server required
- Multiple bindings — Python, Rust, and raw SQL interfaces
openCypher Conformance
GraphQLite is validated against the official openCypher Technology Compatibility Kit (TCK) — the canonical conformance suite for the Cypher query language. Current coverage:
| Area | Scenarios | Passing |
|---|---|---|
| Overall | 3,880 | 98.5% |
| Expressions (temporal, lists, maps, comparison, literals, …) | 2,599 | 98.5% |
| Clauses (MATCH, WITH, MERGE, CREATE, SET, DELETE, UNWIND, …) | 1,251 | 98.6% |
| Use cases (triadic selection, subgraph counting) | 30 | 100% |
Run it yourself with angreal test tck. The remaining gaps are tracked in
docs/testing/semantic-coverage-matrix.md
and concentrate in a few deep areas (DST-aware timezone arithmetic, nested
existential subqueries, multi-row MERGE). Booleans, strings, null handling,
CREATE/SET/DELETE/REMOVE, UNION, and SKIP/LIMIT are at 100%.
Documentation
Full Documentation — Tutorials, how-to guides, and API reference
Examples
# SQL tutorials
sqlite3 < examples/sql/01_getting_started.sql
# GraphRAG with HotpotQA dataset
cd examples/llm-graphrag
uv sync && uv run python ingest.py
uv run python rag.py "Were Scott Derrickson and Ed Wood of the same nationality?"
License
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