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