# Orama — Full-Text and Vector Search Engine for JavaScript

> A fast, typo-tolerant search engine that runs entirely in-process with support for full-text, vector, and hybrid search on any JavaScript runtime.

## Install

Save as a script file and run:

# Orama — Full-Text and Vector Search Engine for JavaScript

## Quick Use
```bash
npm install @orama/orama

node -e "
const { create, insert, search } = require('@orama/orama');
(async () => {
  const db = await create({ schema: { title: 'string', body: 'string' } });
  await insert(db, { title: 'Hello', body: 'World' });
  const results = await search(db, { term: 'hello' });
  console.log(results.hits);
})();
"
```

## Introduction
Orama is an open-source, dependency-free search engine written in TypeScript that supports full-text, vector, and hybrid search. It runs anywhere JavaScript runs — browsers, Node.js, Deno, Bun, and edge runtimes — providing portable search without external services.

## What Orama Does
- Provides sub-millisecond full-text search with built-in typo tolerance and stemming
- Supports vector search and hybrid (keyword + vector) ranking in a single engine
- Runs entirely in-process with no external dependencies or servers required
- Offers faceted search, filters, sorting, grouping, and geo-search
- Includes a plugin system for analytics, persistence, and custom tokenizers

## Architecture Overview
Orama stores documents in an in-memory radix tree for text indexing and flat arrays for vector embeddings. Keyword queries traverse the prefix tree while vector lookups use cosine similarity. Results are scored and merged in a single pass with no network overhead. The index serializes to JSON for persistence.

## Self-Hosting & Configuration
- Install via npm, yarn, or pnpm with no native dependencies
- Import as an ES module or CommonJS package
- Define a schema object describing document fields and types
- Configure custom tokenizers, stemming, or language settings as needed
- Persist indexes using the persistence plugin or manual JSON serialization

## Key Features
- Zero external dependencies; runs on any JavaScript runtime
- Hybrid search combining BM25 full-text ranking with vector similarity
- Built-in typo tolerance with configurable edit distance
- Faceted search, filters, and geo-search out of the box
- Pluggable architecture for extending indexing and search behavior

## Comparison with Similar Tools
- **Lunr.js** — simpler API but lacks vector search, facets, and active maintenance
- **FlexSearch** — fast full-text but no vector or hybrid capabilities
- **MiniSearch** — lightweight but limited to keyword search only
- **Meilisearch** — server-based with broader features but requires a separate process
- **Typesense** — hosted or self-hosted server; Orama runs in-process without infrastructure

## FAQ
**Q: Does Orama require a server?**
A: No. It runs entirely in-process wherever JavaScript runs, including browsers and edge functions.

**Q: Can I use Orama with React or Vue?**
A: Yes. Orama provides framework-agnostic hooks and official integrations for popular frameworks.

**Q: How large can the dataset be?**
A: Browser-side indexes handle tens of thousands of documents; server-side indexes scale to hundreds of thousands.

**Q: Does Orama support multiple languages?**
A: Yes. Built-in stemmers and tokenizers cover 30+ languages.

## Sources
- https://github.com/oramasearch/orama
- https://docs.orama.com

---
Source: https://tokrepo.com/en/workflows/asset-32325e91
Author: Script Depot