search engine (full-text and vector search)
Typesense is a self-hosted search engine offering fast, typo-tolerant full-text, faceting, geosearch, and vector/hybrid search through a simple HTTP API.
Same problem, same approach. Swapping one for another is a config change, not a rewrite.
choose when you want a mature C++/SQL search server with similar full-text and vector/hybrid capabilities and lower operational complexity than a Java stack
Open-source search database for full-text, vector, and hybrid search with real-time indexing and SQL.
choose when you need very large-scale search with advanced ranking and ML features, even though it is heavier to operate than Typesense
The AI search platform
choose when you need an AI-native search database with dense/sparse/tensor vectors and full-text in a C++ engine
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.
choose when you need an all-in-one AI-native search database unifying vector, text, and structured data in a single engine
The AI-Native Search Database. Best for agent storage, it unifies vector, text, structured, and semi-structured data into a single engine. This all-in-one database makes agents smarter, easier to run, and more stable.
choose when you prefer a Rust-based API-first search engine with a similar developer experience and an active ecosystem
A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.
choose when you need hybrid vector+BM25 search with rich object schema and horizontal scaling, accepting more operational complexity
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
choose when you want an embedded search engine in a browser/edge/server library under 2KB instead of a separate service
🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.
choose when you already run Postgres and want full-text and vector search inside that database rather than a dedicated search server
One Postgres for your application data, full-text search, vector retrieval, and aggregations. Home of the pg_search extension.
choose when you want a Rust-based search engine you can embed in-process or run as a small multi-tenant server instead of Typesense's standalone HTTP server
SeekStorm: vector & lexical search - in-process library & multi-tenancy server, in Rust.
choose when you want an embedded retrieval library for local or multimodal search rather than a network search server
Developer-friendly OSS embedded retrieval library for multimodal AI. Search More; Manage Less.
choose when you are in a PHP/SQLite app and want embedded typo-tolerant full-text search without running a separate service
A full text search engine with tokenization, stemming, typo tolerance, filters and geo support based on only PHP and SQLite.
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
choose when you only need high-scale vector similarity search and do not need Typense's typo-tolerant full-text or faceting
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
choose when you want vector search inside Postgres, but it lacks Typesense's full-text and typo-tolerance features
Open-source vector similarity search for Postgres
choose when you need a lightweight embedded vector index only, with no server and no full-text search
A lightweight, lightning-fast, in-process vector database
choose when you need a self-hosted vector-only database and do not need full-text or typo tolerance
Epsilla is a high performance Vector Database Management System
choose when you need distributed vector-only search for AI applications and can live without full-text/typo features
Distributed vector search for AI-native applications
older Postgres vector extension for vector-only workloads; usable but largely unmaintained and without full-text search
PostgreSQL vector database extension for building AI applications
choose for lightweight client-side fuzzy matching over small in-memory data; not a server-side full-text indexer
Lightweight fuzzy-search, in JavaScript
Does the same job, but ships as an app. Useful to a person, not swappable into a codebase.
choose when you want a turnkey enterprise site-search server with crawlers and an admin UI; it is an OpenSearch wrapper, not an embeddable engine
Open-source, self-hosted enterprise & site search server built on OpenSearch. Crawls web / file / DB / cloud sources, 20+ languages, REST API, and AI/RAG & semantic search. Apache-2.0.
These projects were analysed and named typesense among their alternatives. The relationship is not symmetric — how typesense rates them is a separate judgement, made when typesense is analysed in its own right.
calls typesense “Choose Typesense when you want a self-hosted search API with typo tolerance and vector search, likely with different performance and API.”
A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.
calls typesense “Choose when you need an easy-to-use search engine with typo-tolerant full-text and vector search, with a simpler setup than Qdrant.”
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
calls typesense “When you need extremely low-latency, typo-tolerant search on a single node with a simpler API than Elasticsearch.”
Free and Open Source, Distributed, RESTful Search Engine
calls typesense “choose for typo-tolerant full-text and vector search in a single fast search server.”
Open-source vector similarity search for Postgres
calls typesense “when you want a lightweight, typo-tolerant search API with ease of use and vector search built in.”
🦔 Fast, lightweight & schema-less search backend. An alternative to Elasticsearch that runs on a few MBs of RAM.
calls typesense “Choose when you need a high-performance, in-memory search engine as a service, with better scalability than a client-side lib.”
Lightweight fuzzy-search, in JavaScript
calls typesense “Choose when you need fast typo-tolerant full-text search plus vector search with an Algolia-like API.”
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
calls typesense “When you need a fast in-memory typo-tolerant search server with a simple API, GPL/commercial hybrid.”
Tantivy is a full-text search engine library inspired by Apache Lucene and written in Rust
calls typesense “in-memory full-text/vector search server; choose for typo-tolerant search UX in front-end apps.”
A lightweight, lightning-fast, in-process vector database
calls typesense “Choose when you need a fast in-memory server-side search with typo-tolerance and low latency; requires running a separate service.”
Next-generation full-text search library for Browser and Node.js
calls typesense “Choose for in-memory, typo-tolerant, low-latency search with simpler operations, accepting GPL-3.0 and a non-Elasticsearch API.”
🔎 Open source distributed and RESTful search engine.
calls typesense “Choose for typo-tolerant, in-memory search with a simple API; in-memory limits dataset size and uses GPL-3.0.”
Open-source search database for full-text, vector, and hybrid search with real-time indexing and SQL.
calls typesense “Typo-tolerant search server with vector support; choose for fast site search with an API rather than embedded DB.”
Developer-friendly OSS embedded retrieval library for multimodal AI. Search More; Manage Less.
calls typesense “Self-hosted fuzzy search API with vector support; choose when you need in-memory typo-tolerant search as a server.”
🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.
calls typesense “Use when you need an in-memory, low-latency hosted search engine with synonym support.”
A bit like Solr, but much smaller and not as bright
calls typesense “Choose it when you want an in-memory, typo-tolerant search engine with simple deployment and GPL licensing, outside Postgres.”
One Postgres for your application data, full-text search, vector retrieval, and aggregations. Home of the pg_search extension.
calls typesense “Choose for in-memory, low-latency full-text/vector search with simple ops; GPL-3.0 and no distributed ML serving.”
The AI search platform
calls typesense “Search-only engine; choose it for typo-tolerant in-memory full-text/vector search under GPL, not for OLAP/lakehouse workloads.”
Apache Doris is a real-time analytics and hybrid search database for AI agents.