sparq

sparq is a lightning-fast RDF triplestore and SPARQL 1.1 / 1.2 engine, written in Rust — usable as a library, CLI, HTTP server, and from Python and JavaScript/WASM.

Status: experimental research engine. The API is unstable and pre-1.0. Conformance against the W3C SPARQL, SHACL, and inference suites is tracked by CI ratchets that only ever go up — generated by sparq-conformance and published on every run (inference floor committed at inference-conformance-report.md). SPARQL SERVICE federation ships behind the opt-in service cargo feature (off in the default build); when built in it is default-DENY-all egress, allowlisted per host as an SSRF guard (see crates/sparq-server/README.md and research/roadmap.md).

🚀 Quickstart

v0.1.6 release install paths

These are the install commands for the planned v0.1.6 release. Use them only after the tagged release and corresponding registry publications have succeeded. v0.1.5 published the three npm packages but not the PyPI wheels, and the crates.io bootstrap is still pending. Until then, build from source.

# Rust CLI and HTTP server
cargo install sparq-cli --version 0.1.6
cargo install sparq-server --version 0.1.6

# Rust libraries (run inside your Cargo project)
cargo add [email protected] [email protected]

# Python: distribution name sparq-rdf, import name sparq
python -m pip install sparq-rdf==0.1.6
python -c 'import sparq'

# JavaScript/WASM RDF store
npm install @sparq-org/[email protected]
# Loopback-only Solid/LDP development host (not a production server)
npm install @sparq-org/[email protected]
# eye-js / eyereasoner migration API backed by sparq's N3 reasoner
npm install @sparq-org/[email protected]

Build from source

cargo build --release

# Query a file (Turtle / N-Triples / N-Quads / TriG, optionally .gz / .bz2 / .zst)
cargo run --release -p sparq-cli -- query data.ttl turtle \
  'SELECT ?s ?o WHERE { ?s <http://schema.org/name> ?o } LIMIT 10'

# Build a persistent on-disk store once, then query it without loading into RAM
cargo run --release -p sparq-cli -- build data.nt ntriples ./idx
cargo run --release -p sparq-cli -- query-mmap ./idx 'SELECT (COUNT(*) AS ?n) WHERE { ?s ?p ?o }'

# W3C SPARQL Protocol HTTP server on :3030
cargo run --release -p sparq-server -- --addr 127.0.0.1:3030 --format turtle data.ttl

As a library:

use sparq_core::Graph;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let turtle = r#"<http://example.org/alice> a <http://schema.org/Person> ."#;
    let g = Graph::load_str(turtle, "turtle")?;
    let _rows = sparq_engine::query(&g, "SELECT ?s WHERE { ?s a <http://schema.org/Person> }")?;
    let _json = sparq_engine::query_json(&g, "SELECT (COUNT(*) AS ?n) WHERE { ?s ?p ?o }")?;
    Ok(())
}

The CLI, HTTP server, Python (sparq-rdf on PyPI — import sparq), and JS/WASM (@sparq-org/sparq) mirror the same surface. [GPT-5.6] The separate @sparq-org/solid-server package hosts the Solid/LDP wasm adapter for loopback-only local development; @sparq-org/eyereasoner-compat provides an eye-js migration API. Per-surface how-tos live in the usage skills.

✨ Features

The engine core is always built; every other capability is an opt-in crate that the core does not depend on (so it stays lean — enforced in CI). Each capability links its how-to and the standard it implements.

• SPARQL query — run SPARQL 1.1 and 1.2 over your data (guide).
• SPARQL Update — insert, delete, and load data with SPARQL 1.1 Update (guide).
• RDF parsing & ingest — load and parse Turtle, N-Triples, N-Quads, and TriG, with transparent .gz / .bz2 / .zst decompression (guide).
• Rust-native RDF objects — bind a focus term to an owned or borrowed store, traverse outgoing/incoming predicates, and convert typed literal values without handling raw triples (guide).
• RDF 1.2 triple terms — store and query triple terms per RDF 1.2 Concepts (guide).
• Custom extension functions — register your own Rust functions under IRIs and call them in SPARQL (docs/extension-functions.md).
• RDFS / OWL-RL / N3 reasoning — materialise entailments under RDFS, the OWL 2 RL profile, and Notation3 (). N3 is measured against the w3c/N3 community-group suite (); the community suite runs in an advisory lane with no published baseline yet.

• Zero-knowledge query proofs (research scaffold — NOT yet sound) — model proving a query result is correct without revealing the data (guide). The v1 verifier provides no soundness guarantee to a relying party pending external audit — see the security caveat.
• Federated MPC (research scaffold — no security guarantee yet) — model evaluating SPARQL across parties with multi-party computation (guide); honest-majority semi-honest, not maliciously secure (SECURITY.md).

• Interfaces — a CLI, a SPARQL 1.1 Protocol + Graph Store HTTP Protocol HTTP server, a WebAssembly / JavaScript build, and a Python package, plus a Kubernetes Helm deployment.

Agent skills — how to use sparq from Claude Code and other AI agents — are in the usage-skills router.

See AGENTS.md for the full crate map and what each one does.

📚 Learn more

• Use it — AGENTS.md (start here), then skills/SKILL.md, the router pointing at the per-surface usage skill (Rust, CLI, HTTP, Python, JS/WASM, plus reasoning, SHACL, full-text, vector, GeoSPARQL, RSP-QL, ZK query proofs). In Claude Code: /plugin marketplace add sparq-org/sparq then /plugin install sparq@sparq-tools.
• Design — research/ARCHITECTURE.md (blueprint), research/roadmap.md and its completion audit. The research/ tree holds the design notes and measured verdicts for the engine internals.
• Performance — numbers are not baked into the docs (they drift). Live per-commit metrics are at the benchmarks dashboard; the registry and exact invocations are in bench/benchmarks.toml and bench/CATALOG.md. The QLever comparison methodology is in bench/qlever-baselines.md and the continuous Oxigraph differential harness in research/BENCHMARKS.md.
• Trust it — : the 15-minute walkthrough of the assurance estate (conformance ratchets, independent oracles, fuzzing, bounded proofs, honesty gates) — how to check sparq works as claimed without reading the codebase.

Note (crates.io installs): builds installed from crates.io (e.g. cargo install sparq-cli) resolve the upstream spargebra parser — the vendored SPARQL-parser conformance fixes (vendor/spargebra/SPARQ-PATCHES.md) apply only to git builds until the upstream PRs land.

License

MIT.