What is Chroma used for?

Chroma is open-source search infrastructure for AI that stores embeddings and supports vector, hybrid and full-text search, with a small API and a hosted Chroma Cloud. It is a good fit for retrieval layer for RAG applications, memory store for AI agents, and semantic search in prototypes and products.

Is Chroma open source?

Yes. Chroma is open source under the Apache-2.0 licence. Its source code is on GitHub at chroma-core/chroma and is written mainly in Rust.

Yes. Chroma is open source, so the software itself is free to use. A managed cloud version is also available.

Can I self-host Chroma?

Yes. Chroma can be self-hosted on your own server or infrastructure.

What is Chroma an alternative to?

Chroma is an open-source alternative to Pinecone. Other open-source alternatives to Pinecone include Qdrant, Weaviate and Milvus.

Is Chroma actively maintained?

Yes. The most recent commit to Chroma was on 2 October 2026, and the latest release is 1.5.9, published on 5 May 2026. The project has 29k stars on GitHub.

Chroma: open-source alternative to Pinecone

About Chroma

Chroma is open-source data infrastructure for AI applications, centered on storing embeddings and searching them. It supports vector search, hybrid search and full-text search, and its core API is deliberately small, only four functions, so developers can add retrieval to an app quickly. The engine is written in Rust and clients are available through PyPI and npm packages.

For hosting, Chroma Cloud is the company's serverless managed service, which it describes as fast, cost-effective and scalable, and new users can create a database and try it with free starting credits. You can also run Chroma yourself. The project is developing rapidly, and the maintainers release new tagged versions of the Python and npm packages on Mondays, with hotfixes shipped whenever needed.

Chroma is Apache-2.0 licensed. Contributors can join the Discord contributing channel, review the roadmap and pick up good-first issues. Developers use it in retrieval-augmented generation setups, agent memory and semantic search features where they want an easy, embedded-friendly vector store.

Key features

Vector, hybrid and full-text search
Small four-function core API
Python and JavaScript clients
Serverless Chroma Cloud service
Rust core engine
Weekly tagged releases

Good fit for

→Retrieval layer for RAG applications
→Memory store for AI agents
→Semantic search in prototypes and products

Built with: Rust
Tags: vector-database; embeddings; ai; rag; search; rust; agents; semantic-search

Chroma: questions and answers

What is Chroma used for?: Chroma is open-source search infrastructure for AI that stores embeddings and supports vector, hybrid and full-text search, with a small API and a hosted Chroma Cloud. It is a good fit for retrieval layer for RAG applications, memory store for AI agents, and semantic search in prototypes and products.
Is Chroma open source?: Yes. Chroma is open source under the Apache-2.0 licence. Its source code is on GitHub at chroma-core/chroma and is written mainly in Rust.
Is Chroma free?: Yes. Chroma is open source, so the software itself is free to use. A managed cloud version is also available.
Can I self-host Chroma?: Yes. Chroma can be self-hosted on your own server or infrastructure.
What is Chroma an alternative to?: Chroma is an open-source alternative to Pinecone. Other open-source alternatives to Pinecone include Qdrant, Weaviate and Milvus.
Is Chroma actively maintained?: Yes. The most recent commit to Chroma was on 2 October 2026, and the latest release is 1.5.9, published on 5 May 2026. The project has 29k stars on GitHub.