Chroma is the search infrastructure for AI: an open-source embedding database that lets applications store, search and retrieve information by meaning. It is one of the most popular ways to give language models long-term memory and retrieval-augmented generation (RAG) over your own data.
Chroma has collected more than 29,500 stars on GitHub and is a fixture of the AI application stack, with active development continuing through October 2026. The developer experience is deliberately minimal: install the package, create a collection, add documents, and query with natural language; Chroma handles embedding, indexing and similarity search. Under the hood, a Rust core delivers the performance needed for production workloads, and the same API scales from an in-memory prototype to a distributed deployment or the managed Chroma Cloud. It integrates with LangChain, LlamaIndex, OpenAI and most embedding providers, which is why it appears in countless tutorials and production RAG systems alike.
Chroma is free and open source for self-hosting. Chroma Cloud is a paid managed service with usage-based pricing for teams that want serverless scaling without operating the database themselves.
Chroma is for developers building chatbots, semantic search, recommendation features and RAG applications who need a vector database that is trivial to start with and can grow into production without an API change.