MiniSearch is a tiny but powerful in-memory fulltext search engine written in

JavaScript. It is respectful of resources, and it can comfortably run both in

Node and in the browser.

Try out the demo application.

Find the complete [documentation and API reference

here](https://lucaong.github.io/minisearch/classes/_minisearch_.minisearch.html),

and more background about MiniSearch, including a comparison with other

similar libraries, in [this blog

post](https://lucaongaro.eu/blog/2019/01/30/minisearch-client-side-fulltext-search-engine.html).

MiniSearch follows semantic versioning,

and documents releases and changes in the

changelog.

MiniSearch addresses use cases where full-text search features are needed

(e.g. prefix search, fuzzy search, ranking, boosting of fields…), but the data

to be indexed can fit locally in the process memory. While you won't index the

whole Internet with it, there are surprisingly many use cases that are served

well by MiniSearch. By storing the index in local memory, MiniSearch can

work offline, and can process queries quickly, without network latency.

A prominent use-case is real time search "as you type" in web and mobile

applications, where keeping the index on the client enables fast and reactive

UIs, removing the need to make requests to a search server.

  Memory-efficient index, designed to support memory-constrained use cases

    like mobile browsers.

  Exact match, prefix search, fuzzy match, field boosting.

  Auto-suggestion engine, for auto-completion of search queries.

  Modern search result ranking algorithm.

  Documents can be added and removed from the index at any time.

  Zero external dependencies.

MiniSearch strives to expose a simple API that provides the building blocks to

build custom solutions, while keeping a small and well tested codebase.

With npm:

With yarn:

Then require or import it in your project: