Overview: Orama is a lightweight, embeddable search engine built in TypeScript that delivers full-text, vector, and hybrid search capabilities directly in the browser, Node.js, or edge environments. With a footprint under 2KB, it eliminates the need for external search infrastructure while supporting advanced features like geosearch, typo tolerance, and RAG-based chat experiences. Designed for developers building search-rich applications without the overhead of managing separate databases or APIs, Orama enables local indexing and querying with zero dependencies beyond JavaScript/TypeScript runtimes. Its plugin system extends functionality for embeddings, secure API proxies, and data persistence without bloating the core library.
What You Get
- Full-Text Search - Supports BM25 ranking, stemming in 30 languages, typo tolerance, exact match, and field boosting for precise text-based querying.
- Vector Search - Native support for vector embeddings with configurable dimensionality (e.g., vector[1536]), similarity thresholds, and optional embedding inclusion in results.
- Hybrid Search - Combines full-text and vector search by weighting both result sets to improve relevance in semantic and keyword-based queries.
- GenAI Chat Sessions - Built-in RAG pipeline using OpenAI models via Secure Proxy plugin to generate conversational responses from indexed data with source tracking.
- Search Filters - Apply filters on string, number, boolean, enum, and array fields to narrow search results dynamically.
- Geosearch - Perform location-based searches using geopoint fields with latitude and longitude support.
- Pinning Rules (Merchandising) - Force specific documents to appear at the top of search results for promotional or editorial control.
- Facets - Generate dynamic category aggregations from indexed data to enable navigation and filtering interfaces.
- Fields Boosting - Assign higher relevance weights to specific fields (e.g., title over description) during search ranking.
- Plugin System - Extend functionality with official plugins for embeddings, secure API proxies, data persistence, analytics, and framework integrations like Vitepress and Docusaurus.
- Browser-First Deployment - Import directly via CDN in HTML <script type=“module”> or use with Deno and Node.js without build tooling.
- Embedding Generation - Automatically generate text embeddings at insert time using @orama/plugin-embeddings with TensorFlow.js or web-based backends.
Common Use Cases
- Building a client-side product catalog with instant search - A static e-commerce site uses Orama to index 10k+ SKUs locally, enabling instant full-text and filter-based search without backend calls.
- Creating a mobile-first FAQ assistant with RAG - A React Native app embeds Orama to store and search internal documentation, then uses the Secure Proxy plugin to call GPT-4o-mini for conversational answers based on indexed content.
- Problem: Need real-time search in a PWA without a backend → Solution: Orama - A field service app indexes technician notes offline; when connectivity resumes, it syncs and enables full-text/vector search on historical logs without a server dependency.
- Team: Frontend developers building AI features with no DevOps overhead - A small team uses Orama’s plugins to generate embeddings from user-generated content and power semantic search in their Astro-based knowledge base, all without managing a vector database or API keys on the server.
Under The Hood
Orama is a modular, multi-platform search engine and Retrieval-Augmented Generation (RAG) framework built with TypeScript, designed to support diverse deployment environments including browser, server, and edge runtimes. It emphasizes extensibility through plugin architecture and component-based design while offering flexible search capabilities across full-text, vector, and hybrid data models.
Architecture
Orama adopts a modular monorepo structure that enables clear separation of concerns and extensibility across environments.
- Emphasis on strategy-based algorithm selection and tree-structured data handling
- Component-based plugin architecture for flexible integration
- Well-defined modules supporting cross-platform distribution (ESM, CommonJS, Deno)
- Design patterns that promote loose coupling and high cohesion
Tech Stack
Orama leverages TypeScript as its core language with a strong ecosystem for multi-target builds and runtime compatibility.
- Built entirely in TypeScript with support for ESM, CommonJS, and Deno distributions
- Relies on Orama’s internal components, Playwright for testing, TSHY for builds, and SWC for compilation
- Uses Turbo for monorepo management, PNPM for workspace support, and Tap for test execution
- Integrates C8 for code coverage and TSHY for multi-format build configuration
Code Quality
Orama maintains a well-structured codebase with an emphasis on testing and consistent conventions.
- Comprehensive test suite covering various components and edge cases
- Consistent error handling with validation logic and try/catch patterns
- Strong adherence to naming standards and modular architecture principles
- Some technical debt evident in duplicated logic and complex customization paths
What Makes It Unique
Orama distinguishes itself through its unified approach to multi-modal search and RAG workflows.
- Combines full-text, vector, and hybrid search in a single extensible framework
- Offers plugin-driven architecture for customizing search behavior and data models
- Designed for seamless deployment across browser, server, and edge environments
- Focuses on developer ergonomics with component-based extensibility