Vector databases: 38 open-source projects (2026)

Distributed, RESTful search and analytics engine that also serves as a scalable data store and vector database.

An in-memory data store used as a cache, data structure server, document store, vector database, and message broker.

A fast, typo-tolerant search engine with API that supports full-text, semantic, and hybrid search for websites and apps.

Milvus is an open-source, distributed vector database for storing and searching embeddings at scale, used for AI search and RAG applications.

A C++ library with Python bindings for efficient similarity search and clustering of dense vectors, with optional GPU acceleration.

Qdrant is a Rust-based vector similarity search engine and vector database with payload filtering, for semantic search and recommendation.

A local, on-device CLI search engine for markdown notes, meeting transcripts and docs, combining BM25, vector search and LLM reranking.

Open-source embedding database for AI apps, storing documents and vectors to power semantic, hybrid and full-text search.

Typesense is an open-source, in-memory search engine with typo tolerance, faceting, geo search and vector search, aimed at being a simpler alternative to Algolia and Elasticsearch.

Open-source vector similarity search extension for Postgres, storing and querying embeddings alongside your relational data.

An in-process vector index for Python and Rust that compresses embeddings to 2 or 4 bits per dimension using TurboQuant and searches them directly.

Open-source vector database that stores objects and vectors together, combining vector similarity search with structured filtering.

An open-source, in-process vector database that embeds directly into applications for low-latency similarity search without running a server.

A local vector index and RAG toolkit that cuts storage by about 97% by recomputing embeddings on demand, so you can search personal data on your laptop.

Open-source search database supporting full-text, vector and hybrid search with real-time indexing and SQL, positioned as an Elasticsearch alternative.

An embedded retrieval library and database for multimodal AI, offering vector, full-text and SQL search over data stored in the Lance format.

A JavaScript/TypeScript search engine library that runs in the browser, Node.js, or edge runtimes, supporting full-text, vector, and hybrid search.

A Postgres extension that adds full-text search, vector search, BM25 scoring and aggregations to your existing Postgres database.

An open lakehouse table and file format for multimodal AI, with vector search, full-text search, and fast random access on object storage.

Vespa is an open-source search engine and serving platform for vectors, tensors, text and structured data at scale.

An open-source graph database in Rust that stores graph, vector and full-text data together on object storage, queryable from Rust, TypeScript, Go and Python.

A Redis module that adds full-text, secondary indexing, vector similarity and aggregation queries to Redis data.

A MySQL 8.0.44 branch from Alibaba Cloud adding a DuckDB analytical storage engine, HNSW vector indexes, and native flashback queries.

Header-only C++ library with Python bindings for fast approximate nearest neighbor search using the HNSW graph algorithm.

A C++ library for large-scale approximate nearest neighbor vector search, with index build, search, and distributed serving toolkits.

An AI-native database for LLM applications, offering hybrid search over dense vectors, sparse vectors, tensors and full-text.

A single-file C++ library for approximate nearest-neighbor vector search and clustering, with bindings for Python, JavaScript, Rust, Java, Go, Swift and more.

An AI-native search database that stores vector, full-text, structured and semi-structured data in one MySQL-compatible engine, for agent memory and retrieval.

A Postgres extension in Rust that adds a DiskANN-based index and label filtering on top of pgvector for faster, cheaper vector search.

In-process Rust library and multi-tenant server for lexical, vector and hybrid search, with an MCP server for AI agents.