speedkey

March 27, 2026 · View on GitHub

Valkey/Redis client with direct NAPI bindings based on valkey-glide core. No IPC socket - Rust talks directly to Node.js via NAPI.

This is the client layer for glide-mq. It will be replaced by the official valkey-glide NAPI client once it ships upstream. Until then, speedkey provides the same typed API surface that glide-mq depends on.

Note: speedkey will be replaced by valkey-glide when glide completes its migration to NAPI. The API surface is designed to align with valkey-glide to minimize migration effort.

Install

npm install @glidemq/speedkey

Requires valkey-bundle for Search, JSON, and Bloom module support:

docker run -d -p 6379:6379 valkey/valkey-bundle

Module Support

Search (GlideFt) - 5 commands

Command	Method	Description
`FT.CREATE`	`GlideFt.create()`	Create a search index with HASH or JSON schema
`FT.SEARCH`	`GlideFt.search()`	Search an index with filters and KNN vector queries
`FT.DROPINDEX`	`GlideFt.dropindex()`	Delete an index
`FT.INFO`	`GlideFt.info()`	Get index metadata
`FT._LIST`	`GlideFt.list()`	List all indexes

Search 1.1/1.2 options supported:

FT.CREATE: score, language, skipInitialScan, minStemSize, withOffsets/noOffsets, noStopWords/stopWords, punctuation. Fields: sortable, nostem, weight, withsuffixtrie/nosuffixtrie.

FT.SEARCH: nocontent, dialect, verbatim, inorder, slop, sortby, scorer.

Not available in valkey-search: FT.AGGREGATE, FT.EXPLAIN, FT.EXPLAINCLI, FT.PROFILE, FT.ALIASADD, FT.ALIASDEL, FT.ALIASUPDATE, FT._ALIASLIST. These are Redis Search (redis-stack) only.

JSON (GlideJson) - 22 commands

Full JSON document manipulation: SET, GET, MGET, MSET, DEL, FORGET, TYPE, CLEAR, TOGGLE, STRLEN, STRAPPEND, ARRAPPEND, ARRINSERT, ARRLEN, ARRPOP, ARRTRIM, ARRINDEX, NUMINCRBY, NUMMULTBY, OBJLEN, OBJKEYS, RESP, DEBUG.

Bloom Filter (GlideBf) - 9 commands

Command	Method	Description
`BF.RESERVE`	`GlideBf.reserve()`	Create a bloom filter with error rate and capacity
`BF.ADD`	`GlideBf.add()`	Add an item (returns true if new)
`BF.MADD`	`GlideBf.madd()`	Add multiple items
`BF.EXISTS`	`GlideBf.exists()`	Check if item may exist
`BF.MEXISTS`	`GlideBf.mexists()`	Check multiple items
`BF.INFO`	`GlideBf.info()`	Get filter metadata
`BF.INSERT`	`GlideBf.insert()`	Add items with auto-create options
`BF.CARD`	`GlideBf.card()`	Get item count
`BF.LOAD`	`GlideBf.load()`	Restore a serialized filter

Usage

import {
  GlideClient,
  GlideClusterClient,
  GlideJson,
  GlideFt,
  GlideBf,
} from "@glidemq/speedkey";

// Standalone
const client = await GlideClient.createClient({
  addresses: [{ host: "localhost", port: 6379 }],
});

// Cluster
const cluster = await GlideClusterClient.createClient({
  addresses: [{ host: "127.0.0.1", port: 7000 }],
});

JSON

await GlideJson.set(client, "user:1", "$", '{"name":"Alice","age":30}');
const user = await GlideJson.get(client, "user:1", { path: "$" });

// Batch set
await GlideJson.mset(client, [
  { key: "user:2", path: "$", value: '{"name":"Bob"}' },
  { key: "user:3", path: "$", value: '{"name":"Carol"}' },
]);

Vector Search

// Create index with vector field (required by valkey-search)
await GlideFt.create(client, "docs-idx", [
  { type: "TAG", name: "category" },
  { type: "NUMERIC", name: "score" },
  {
    type: "VECTOR", name: "embedding",
    attributes: {
      algorithm: "HNSW",
      dimensions: 384,
      distanceMetric: "COSINE",
      type: "FLOAT32",
    },
  },
], { dataType: "HASH", prefixes: ["doc:"] });

// Store document with embedding
const embedding = new Float32Array(384); // from your embedding model
await client.hset("doc:1", {
  category: "ml",
  score: "95",
  embedding: Buffer.from(embedding.buffer),
});

// KNN search with pre-filter
const [total, results] = await GlideFt.search(
  client, "docs-idx",
  "@category:{ml}=>[KNN 5 @embedding $VEC AS dist]",
  { params: [{ key: "VEC", value: Buffer.from(embedding.buffer) }] },
);

Bloom Filter

await GlideBf.reserve(client, "emails", 0.001, 100000);
await GlideBf.add(client, "emails", "alice@example.com");

const exists = await GlideBf.exists(client, "emails", "alice@example.com"); // true
const missing = await GlideBf.exists(client, "emails", "unknown@x.com");   // false

const info = await GlideBf.info(client, "emails");
// { capacity: 100000, size: ..., numberOfFilters: 1, numberOfItems: 1, expansionRate: 2 }

Core API

speedkey exposes the full valkey-glide BaseClient API (200+ commands) for strings, hashes, lists, sets, sorted sets, streams, HyperLogLog, geo, pub/sub, scripting, and more. See the valkey-glide documentation for the complete command reference.

License

Apache-2.0