corvid-node

corvid-node is the Node.js binding: the engine compiled in (a Rust napi crate pinned to an exact corvid release tag), exposed as idiomatic synchronous OOP — Db, Collection, a fluent Query builder, and field() predicates. No SQL, no JSON, no serialization on the data path; values map natively.

When to choose this binding: your application is Node.js (servers, CLIs, tooling) and you want an embedded database with vector/text/hybrid search, graph edges, and geo — without running a separate database server. The engine compiles into the process (a prebuilt native binary per platform), calls are synchronous, and JavaScript values cross the boundary natively. For browsers, wait for the planned wasm binding; for a system library you can link from anything, see corvid-c.

Install

npm i corvid-node

Pending first publish — the package is not on npm yet; publishing waits on the platform packages existing first (the repo’s plan §5). Until then build from source (Rust ≥ 1.88 + a C toolchain):

npm install
npm run build

Prebuilt binaries (optionalDependencies) will cover darwin-arm64 / darwin-x64 / linux-x64-gnu / linux-arm64-gnu / win32-x64-msvc.

The examples

Six runnable programs in the repo’s examples/ directory, executed on every CI leg with deterministic output: quickstart, hybrid (the flagship below), vector-index (in-memory / on-disk / binary-quantized HNSW vs the exact scan), text-search (BM25 incl. CJK bigram segmentation, plus the v0.3.0 direct phraseSearch()), graph (neighbors/traverse + delete cascade), and geo (radius / bbox / nearest). The quickstart and hybrid sources are embedded below — imported from the repo so they cannot drift from what CI executes (scripts/sync-binding-examples.sh; the drift gate reddens docs CI if they diverge). Run them from a checkout with npm run build && node examples/hybrid.js (they require('..'); in an application, require('corvid-node')).

Quickstart

const { Db } = require('..');

const db = Db.openMemory();
const docs = db.collection('docs');

docs.insert('p1', {
  title: 'rust embedded database',
  kind: 'doc',
  v: new Float32Array([1.0, 0.0]),
});
docs.insert('p2', {
  title: 'python web frameworks',
  kind: 'doc',
  v: new Float32Array([0.0, 1.0]),
});
docs.insert('p3', {
  title: 'rust again database',
  kind: 'doc',
  v: new Float32Array([0.9, 0.1]),
});

// kNN: the 3 nearest documents to (1, 0) under cosine.
const rows = docs
  .query()
  .vector('v', new Float32Array([1.0, 0.0]), 3, 'cosine')
  .run(); // [{ key, doc, score }]

let rank = 0;
for (const { key, doc, score } of rows) {
  console.log(`${++rank}. ${key} score=${score.toFixed(6)} ${doc.title}`);
}

docs.close();
db.close();

Hybrid retrieval

const { Db, field } = require('..');

const db = Db.openMemory();
const docs = db.collection('docs');

docs.insert('s1', { kind: 'doc', body: 'rust embedded database', v: new Float32Array([1.0, 0.0]) });
docs.insert('s2', { kind: 'doc', body: 'python web frameworks', v: new Float32Array([0.0, 1.0]) });
docs.insert('s3', { kind: 'doc', body: 'rust again database', v: new Float32Array([0.9, 0.1]) });
docs.insert('m1', { kind: 'meta' }); // filtered out below

// The flagship query: filter + vector + text, RRF + MMR + limit.
const rows = docs
  .query()
  .filter(field('kind').eq('doc'))
  .vector('v', new Float32Array([1.0, 0.0]), 2, 'cosine')
  .text('body', 'rust database', 2)
  .fuseRrf(60)
  .rerankMmr(1.0)
  .limit(2)
  .run(); // [{ key, doc, score }]

let rank = 0;
for (const { key, doc, score } of rows) {
  console.log(`${++rank}. ${key} score=${score.toFixed(6)} ${doc.body}`);
}

docs.close();
db.close();

The fused scores are RRF rank sums: s1 is rank 1 of both sources (1/61 + 1/61 = 2/61 ≈ 0.032787), s3 rank 2 of both (2/62 ≈ 0.032258).

Value mapping

JS	engine
null, boolean, string	Null / Bool / Text
number (integer-valued, ≤ 2^53)	Int — 2 and 2.0 collapse; CorvidFloat(n) forces the Float kind
number (0.5, inf, NaN, -0.0), bigint	Float / Int (full i64)
Buffer / Uint8Array	Bytes
Float32Array	Vector
Array / plain object	Array / Map

Reading back: Int → number (or bigint beyond ±2^53); Float → number with f64 bits preserved except NaN payloads, which V8 canonicalizes at the N-API number boundary (-0.0, ±inf are exact; vector elements keep their f32 bits). Keys are strings (UTF-8) or Buffers.

Correctness story

The binding replays the engine’s golden suite — the same 267-line fixture files the C ABI smoke harness runs — against its public API on every CI run (test/golden.spec.ts), then executes the six-example tour. The plan (architecture ruling, OOP surface, value contract, follow-ups) lives in the repo.

Development

npm install                 # @napi-rs/cli + vitest
npm run build               # build the native binary for this platform
npm test                    # the golden suite (267 lines)
node examples/hybrid.js     # the examples tour
npm run lint                # cargo fmt --check + clippy -D warnings

Next: corvid-python.