git-subtree-dir: vendor/ruvector git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900
@ruvector/rvf-node
Native Node.js bindings for the RuVector Format (RVF) vector database. Built with Rust via N-API for native speed with zero serialization overhead.
Install
npm install @ruvector/rvf-node
Features
- Native Rust performance via N-API (napi-rs), no FFI marshaling
- Single-file vector database — crash-safe, no WAL, append-only
- k-NN search with HNSW progressive indexing (recall 0.70 → 0.95)
- Metadata filtering — Eq, Ne, Lt, Gt, Range, In, And, Or, Not
- Lineage tracking — DNA-style parent/child derivation chains
- Kernel & eBPF embedding — embed compute alongside vector data
- Segment inspection — enumerate all segments in the file
- Cross-platform — Linux (x86_64, aarch64), macOS (x86_64, Apple Silicon), Windows (x86_64)
Quick Start
const { RvfDatabase } = require('@ruvector/rvf-node');
// Create a store
const db = RvfDatabase.create('vectors.rvf', {
dimension: 384,
metric: 'cosine',
});
// Insert vectors
const vectors = new Float32Array(384 * 2); // 2 vectors, 384 dims each
vectors.fill(0.1);
db.ingestBatch(vectors, [1, 2]);
// Query nearest neighbors
const query = new Float32Array(384);
query.fill(0.15);
const results = db.query(query, 5);
// [{ id: 1, distance: 0.002 }, { id: 2, distance: 0.002 }]
db.close();
API Reference
Store Lifecycle
// Create a new store
const db = RvfDatabase.create(path: string, options: RvfOptions);
// Open existing store (read-write, acquires writer lock)
const db = RvfDatabase.open(path: string);
// Open read-only (no lock, concurrent readers allowed)
const db = RvfDatabase.openReadonly(path: string);
// Close and flush
db.close();
RvfOptions:
| Field | Type | Default | Description |
|---|---|---|---|
dimension |
number |
required | Vector dimensionality |
metric |
string |
"l2" |
"l2", "cosine", or "inner_product" |
profile |
number |
0 |
Hardware profile: 0=Generic, 1=Core, 2=Hot, 3=Full |
signing |
boolean |
false |
Enable segment signing |
m |
number |
16 |
HNSW M parameter (neighbor count) |
efConstruction |
number |
200 |
HNSW index build quality |
Ingest Vectors
const result = db.ingestBatch(
vectors: Float32Array, // flat array of n * dimension floats
ids: number[], // vector IDs
metadata?: RvfMetadataEntry[] // optional metadata per vector
);
// Returns: { accepted: number, rejected: number, epoch: number }
Metadata entry format:
{ fieldId: 0, valueType: 'string', value: 'category_a' }
{ fieldId: 1, valueType: 'f64', value: '0.95' }
{ fieldId: 2, valueType: 'u64', value: '42' }
Query
const results = db.query(
vector: Float32Array, // query vector
k: number, // number of neighbors
options?: RvfQueryOptions // optional search parameters
);
// Returns: [{ id: number, distance: number }, ...]
RvfQueryOptions:
| Field | Type | Default | Description |
|---|---|---|---|
efSearch |
number |
100 |
HNSW search quality (higher = better recall, slower) |
filter |
string |
— | Filter expression as JSON string |
timeoutMs |
number |
0 |
Query timeout in ms (0 = no timeout) |
Filter Expressions
Filters are passed as JSON strings. All leaf filters require fieldId, valueType, and value:
// Equality
db.query(vec, 10, {
filter: '{"op":"eq","fieldId":0,"valueType":"string","value":"science"}'
});
// Range
db.query(vec, 10, {
filter: '{"op":"range","fieldId":1,"valueType":"f64","low":"0.5","high":"1.0"}'
});
// In-set
db.query(vec, 10, {
filter: '{"op":"in","fieldId":0,"valueType":"u64","values":["1","2","5"]}'
});
// Boolean combinations
db.query(vec, 10, {
filter: JSON.stringify({
op: 'and',
children: [
{ op: 'eq', fieldId: 0, valueType: 'string', value: 'science' },
{ op: 'gt', fieldId: 1, valueType: 'f64', value: '0.8' }
]
})
});
// Negation
db.query(vec, 10, {
filter: '{"op":"not","child":{"op":"eq","fieldId":0,"valueType":"string","value":"spam"}}'
});
Supported operators: eq, ne, lt, le, gt, ge, in, range, and, or, not
Supported value types: u64, i64, f64, string, bool
Delete
// Delete by ID
const result = db.delete([1, 2, 3]);
// Returns: { deleted: number, epoch: number }
// Delete by filter
const result = db.deleteByFilter(
'{"op":"gt","fieldId":1,"valueType":"f64","value":"0.9"}'
);
Compact
Reclaims space from deleted vectors:
const result = db.compact();
// Returns: { segmentsCompacted: number, bytesReclaimed: number, epoch: number }
Status
const status = db.status();
// {
// totalVectors: number,
// totalSegments: number,
// fileSize: number,
// currentEpoch: number,
// profileId: number,
// compactionState: 'idle' | 'running' | 'emergency',
// deadSpaceRatio: number,
// readOnly: boolean
// }
Lineage & Derivation
RVF tracks parent/child relationships with cryptographic hashes:
db.fileId(); // hex string — unique file identifier
db.parentId(); // hex string — parent's ID (zeros if root)
db.lineageDepth(); // 0 for root files
// Derive a child store (inherits dimensions and options)
const child = db.derive('/tmp/child.rvf');
child.lineageDepth(); // 1
child.parentId(); // matches parent's fileId()
Kernel & eBPF Embedding
Embed compute segments alongside vector data:
// Embed a Linux microkernel
db.embedKernel(
1, // arch: 0=x86_64, 1=aarch64
0, // kernel type
0, // flags
Buffer.from(kernelImage), // kernel binary
8080, // API port
'console=ttyS0 quiet' // kernel cmdline (optional)
);
// Extract kernel
const kernel = db.extractKernel();
if (kernel) {
console.log(kernel.header); // Buffer: 128-byte KernelHeader
console.log(kernel.image); // Buffer: kernel image bytes
}
// Embed an eBPF XDP program
db.embedEbpf(
1, // program type (XDP distance)
2, // attach type (XDP ingress)
384, // max vector dimension
Buffer.from(bytecode), // BPF ELF object
Buffer.from(btf) // optional BTF section
);
// Extract eBPF
const ebpf = db.extractEbpf();
if (ebpf) {
console.log(ebpf.header); // Buffer: 64-byte EbpfHeader
console.log(ebpf.payload); // Buffer: bytecode + BTF
}
Segment Inspection
const segments = db.segments();
// [{ id: 1, offset: 0, payloadLength: 4096, segType: 'manifest' },
// { id: 2, offset: 4160, payloadLength: 51200, segType: 'vec' },
// { id: 3, offset: 55424, payloadLength: 12288, segType: 'index' }]
db.dimension(); // 384
Build from Source
# Prerequisites: Rust 1.87+, Node.js 18+
cd crates/rvf/rvf-node
npm install
npm run build
Related Packages
| Package | Description |
|---|---|
@ruvector/rvf |
Unified TypeScript SDK |
@ruvector/rvf-wasm |
Browser WASM package |
@ruvector/rvf-mcp-server |
MCP server for AI agents |
rvf-runtime |
Rust runtime (powers this package) |
License
MIT OR Apache-2.0