Native Node.js bindings for RuVector Graph Database with hypergraph support, Cypher queries, and persistence - 10x faster than WASM
npm install @ruvector/graph-nodeNative Node.js bindings for RuVector Graph Database with hypergraph support, Cypher queries, and persistence. 10x faster than WASM.
- Native Performance: Direct NAPI-RS bindings - no WASM overhead
- Hypergraph Support: Multi-node relationships with vector embeddings
- Cypher Queries: Neo4j-compatible query language
- Persistence: ACID-compliant storage with redb backend
- Vector Similarity Search: Fast k-NN search on embeddings
- Graph Traversal: k-hop neighbor discovery
- Transactions: Full ACID support with begin/commit/rollback
- Batch Operations: High-throughput bulk inserts (131K+ ops/sec)
- Zero-Copy: Efficient Float32Array handling
- TypeScript: Full type definitions included
``bash`
npm install @ruvector/graph-node
`javascript
const { GraphDatabase } = require('@ruvector/graph-node');
// Create an in-memory database
const db = new GraphDatabase({
distanceMetric: 'Cosine',
dimensions: 384
});
// Or create a persistent database
const persistentDb = new GraphDatabase({
distanceMetric: 'Cosine',
dimensions: 384,
storagePath: './my-graph.db'
});
// Or open an existing database
const existingDb = GraphDatabase.open('./my-graph.db');
// Create nodes
await db.createNode({
id: 'alice',
embedding: new Float32Array([1.0, 0.0, 0.0, / ... /]),
labels: ['Person', 'Employee'],
properties: { name: 'Alice', age: '30' }
});
// Create edges
await db.createEdge({
from: 'alice',
to: 'bob',
description: 'KNOWS',
embedding: new Float32Array([0.5, 0.5, 0.0, / ... /]),
confidence: 0.95
});
// Create hyperedges (multi-node relationships)
await db.createHyperedge({
nodes: ['alice', 'bob', 'charlie'],
description: 'COLLABORATED_ON_PROJECT',
embedding: new Float32Array([0.33, 0.33, 0.33, / ... /]),
confidence: 0.85
});
// Query with Cypher
const results = await db.query('MATCH (n:Person) RETURN n');
// Vector similarity search
const similar = await db.searchHyperedges({
embedding: new Float32Array([0.3, 0.3, 0.3, / ... /]),
k: 10
});
// Get statistics
const stats = await db.stats();
console.log(\Nodes: \${stats.totalNodes}, Edges: \${stats.totalEdges}\);``
| Operation | Throughput | Latency |
|-----------|------------|---------|
| Node Creation | 9.17K ops/sec | 109ms |
| Batch Node Creation | 131.10K ops/sec | 7.63ms |
| Edge Creation | 9.30K ops/sec | 107ms |
| Vector Search (k=10) | 2.35K ops/sec | 42ms |
| k-hop Traversal | 10.28K ops/sec | 9.73ms |
| Platform | Architecture | Status |
|----------|--------------|--------|
| Linux | x64 (glibc) | Supported |
| Linux | arm64 (glibc) | Supported |
| macOS | x64 | Supported |
| macOS | arm64 (M1/M2) | Supported |
| Windows | x64 | Supported |
MIT