FrozenMiniSearch

API documentation · Live demo

Memory-optimized, read-only full-text search for Node.js and browsers. FrozenMiniSearch is built for fixed corpora, with compact immutable indexes and MiniSearch-compatible query semantics.

Try the demo application (Billboard Hot 100 search and auto-suggest in the browser).

Use it when your documents are built offline, shipped to production, and queried many times. In that shape, frozen indexes use ~94–95% less index RAM (totalResident = heapUsed + external on both sides) in the main benchmark set, save to compact binary snapshots, and load faster than MiniSearch JSON.

This package is intentionally focused on fixed-corpus serving: build frozen directly, persist binary snapshots, then load and query them many times.

Why FrozenMiniSearch?

FrozenMiniSearch is for the common production path where search data changes elsewhere, not inside the web process:

• Build or import the index offline.
• Save it as a compact binary snapshot.
• Load it in many read-only Node.js processes.
• Query with MiniSearch-compatible search, autoSuggest, filters, boosts, prefix/fuzzy search, wildcard, and AND / OR / AND_NOT.

Internally it uses packed radix postings, typed arrays, and columnar stored fields instead of large JavaScript object graphs. The result is a search engine tuned for resident efficiency, fast loads, and repeatable serving workflows.

Measured vs MiniSearch

On the main benchmark set vs MiniSearch 7.2.0, frozen indexes use ~95% less index RAM and win on 27/27 search cases.

Full comparison table, column definitions, and capture metadata: benchmarks/VS_REFERENCE.md (benchmarks/baselines/reference.json @ 1cdc405, 2026-07-04).

Quick start

pnpm add @yoch/frozenminisearch

import FrozenMiniSearch from '@yoch/frozenminisearch'

const options = { fields: ['title', 'text'], storeFields: ['title'] }
const index = FrozenMiniSearch.fromDocuments(documents, options)

index.search('ishmael', { prefix: true })
index.autoSuggest('zen ar')

const buf = index.saveBinarySync()
const loaded = FrozenMiniSearch.loadBinarySync(buf, options)

For larger imports, use the incremental builder:

import FrozenMiniSearch, {
  createFrozenIndexBuilder,
  freezeFrozenIndexBuilder,
} from '@yoch/frozenminisearch'

const builder = createFrozenIndexBuilder(options, { estimatedDocumentCount: rows.length })
builder.addAll(rows) // `addAllAsync` for chunked, non-blocking ingestion (browser)
const index = freezeFrozenIndexBuilder(builder)

ESM and CommonJS are both supported on Node (main → CJS, module → ESM). For browsers and bundlers, use the dedicated browser entry (search, build, and async binary I/O):

import FrozenMiniSearch from '@yoch/frozenminisearch/browser'

const index = FrozenMiniSearch.fromDocuments(documents, options)
index.search('ishmael', { prefix: true })

// Load a zlib snapshot from CDN (Uint8Array)
const buf = new Uint8Array(await (await fetch('/index.frozen')).arrayBuffer())
const loaded = await FrozenMiniSearch.loadBinaryAsync(buf, options)

See the hosted demo or examples/plain_js_frozen/README.md locally (pnpm docs:demo:frozen then serve the repo root).

Usage

Basic usage

const documents = [
  { id: 1, title: 'Moby Dick', text: 'Call me Ishmael. Some years ago...', category: 'fiction' },
  { id: 2, title: 'Zen and the Art of Motorcycle Maintenance', text: 'I can see by my watch...', category: 'fiction' },
  // ...
]

const options = { fields: ['title', 'text'], storeFields: ['title', 'category'] }
const index = FrozenMiniSearch.fromDocuments(documents, options)

index.search('zen art motorcycle')
// => [{ id, title, category, score, match, ... }, ...]

Frozen indexes are read-only: there is no add, remove, or discard. Rebuild offline or use createFrozenIndexBuilder for incremental ingestion before finalizing the index.

Search options

MiniSearch-compatible options work on search() and autoSuggest():

index.search('zen', { fields: ['title'] })
index.search('zen', { boost: { title: 2 } })
index.search('moto', { prefix: true })
index.search('ismael', { fuzzy: 0.2 })
index.search('zen', { filter: (result) => result.category === 'fiction' })
index.search('zen', { combineWith: 'AND' }) // OR, AND_NOT

const index = FrozenMiniSearch.fromDocuments(documents, {
  fields: ['title', 'text'],
  searchOptions: { prefix: true, fuzzy: 0.2 },
})

Wildcard and nested query combinations are supported (FrozenMiniSearch.wildcard, QueryCombination).

Auto-suggestions

index.autoSuggest('zen ar')
// => [{ suggestion: 'zen archery art', terms: [...], score }, ...]

index.autoSuggest('neromancer', { fuzzy: 0.2 })
index.autoSuggest('zen ar', { filter: (result) => result.category === 'fiction' })

Field extraction

For nested or computed fields, pass extractField at index build time (and again when loading binary snapshots if you override defaults):

const options = {
  fields: ['title', 'author.name', 'pubYear'],
  extractField: (document, fieldName) => {
    if (fieldName === 'pubYear') {
      return document.pubDate?.getFullYear().toString()
    }
    return fieldName.split('.').reduce((doc, key) => doc && doc[key], document)
  },
}

The default extractor is available via FrozenMiniSearch.getDefault('extractField').

Tokenization

const options = {
  fields: ['title', 'text'],
  tokenize: (string, _fieldName) => string.split('-'),
  searchOptions: {
    tokenize: (string) => string.split(/[\s-]+/),
  },
}

FrozenMiniSearch.getDefault('tokenize') returns the built-in Unicode space/punctuation splitter. Only that exact function reference enables the fastest indexing path; equivalent wrappers use the general path.

Term processing

const stopWords = new Set(['and', 'or', 'the'])

const options = {
  fields: ['title', 'text'],
  processTerm: (term) => (stopWords.has(term) ? null : term.toLowerCase()),
  searchOptions: {
    processTerm: (term) => term.toLowerCase(),
  },
}

FrozenMiniSearch.getDefault('processTerm') downcases terms (no stemming or stop-word list by default).

Default helpers

FrozenMiniSearch.getDefault('tokenize')
FrozenMiniSearch.getDefault('processTerm')
FrozenMiniSearch.getDefault('extractField')
FrozenMiniSearch.getDefault('stringifyField')

Use these when wrapping a custom function and delegating to the library default.

Migration and interoperability

For fixed corpora, most serving code can stay the same. Change how the index is built or loaded, then keep calling search, autoSuggest, has, and getStoredFields.

Default and named imports both work:

// ESM
import FrozenMiniSearch from '@yoch/frozenminisearch'
import { FrozenMiniSearch } from '@yoch/frozenminisearch'

// CommonJS
const FrozenMiniSearch = require('@yoch/frozenminisearch')
const { FrozenMiniSearch } = require('@yoch/frozenminisearch')

The native workflow is to build frozen directly:

import FrozenMiniSearch from '@yoch/frozenminisearch'

const frozen = FrozenMiniSearch.fromDocuments(documents, options)

Existing MiniSearch JSON snapshots can be imported through the compatibility path:

import MiniSearch from 'minisearch'
import FrozenMiniSearch from '@yoch/frozenminisearch'

const upstream = new MiniSearch(options)
upstream.addAll(documents)

const frozen = FrozenMiniSearch.fromJSON(JSON.stringify(upstream), options)

This path is useful for migration and interchange. In normal frozen deployments, you typically build with fromDocuments, the builder API, or binary snapshots directly. Internally, fromJSON now packs terms directly into the immutable packed term index; it no longer routes through any local SearchableMap or mutable radix fallback.

Search API (MiniSearch-compatible)

• search(query, searchOptions?) — string, wildcard (FrozenMiniSearch.wildcard), or nested QueryCombination
• autoSuggest(queryString, options?)
• has(id), getStoredFields(id)
• getDefault(optionName) — built-in tokenize, processTerm, extractField, stringifyField, …
• saveBinarySync / loadBinarySync on Node (async variants too); browser entry supports async binary only (Uint8Array, raw / zlib / auto)

Custom tokenize and processTerm functions are not stored in snapshots; pass the same functions again when loading.

See Usage above for examples.

Binary snapshots (Node)

Binary snapshots are the preferred production format on Node.js.

const buf = index.saveBinarySync()
const loaded = FrozenMiniSearch.loadBinarySync(buf, {}) // field names embedded in snapshot

• Node ≥ 20
• compression: 'auto' uses zlib when it shrinks the payload (portable on Node 20+ and in the browser build); falls back to raw when compression does not help.
• Use explicit compression when you need a specific artifact:

const portable = index.saveBinarySync({ compression: 'zlib' }) // CDN / browser
const uncompressed = index.saveBinarySync({ compression: 'raw' })
const bestRatio = index.saveBinarySync({ compression: 'zstd' }) // Node 22.15+ only

Raw snapshots load in the browser without native compression APIs. zlib snapshots in the browser require CompressionStream / DecompressionStream. Browser binary I/O is async because it uses native browser stream APIs, but it still materializes the full compressed/decompressed payload in memory. zstd snapshots require Node 22.15+ (read/write on Node; not supported in the browser build).

Benchmarks

See benchmarks/README.md.

pnpm bench                                 # quick smoke (dev profile)
pnpm bench:run                             # full suite (regression profile)
NODE_OPTIONS='--expose-gc' node benchmarks/framework/cli.mjs run --profile=vs-reference
pnpm bench:record && pnpm bench:diff       # capture then diff vs reference.json
node benchmarks/scripts/generate-readme-comparison.mjs --from=benchmarks/baselines/latest.json

Development

pnpm install
pnpm test          # src/ + dev/parity/
pnpm build
node scripts/verify-npm-pack.cjs

Parity tests compare against MiniSearch 7. Longer notes and performance work live under dev/docs/ (repository only) and benchmarks/README.md.

Changelog & credits

See CHANGELOG.md.

• MiniSearch — Luca Ongaro (MIT)
• @yoch/frozenminisearch — memory-optimized frozen indexes and compact binary snapshots

Upstream docs: MiniSearch