Chroma
The open-source embedding database for AI apps — add search, memory and retrieval to an LLM in a few lines of code, then self-host it as a Pinecone alternative.
Pinecone
WeaviateAbout Chroma
Chroma is the database you reach for when an LLM app needs to remember things. It stores embeddings alongside documents and metadata, so you can run semantic search, retrieval-augmented generation and long-term memory without standing up heavy infrastructure first.
The whole point is how little ceremony it takes: pip install, create a collection, add your documents, and query — a working retrieval layer in a few lines of Python or JavaScript. It runs in-process for prototyping and scales out to a self-hosted server as your app grows.
Because it's Apache-2.0 licensed and self-hostable, your embeddings and documents stay on your own infrastructure — the core reason AI teams move off hosted vector databases like Pinecone. The core is being rewritten in Rust for performance while keeping the same simple client API.
Key features
- Embeddings built in — Bring your own vectors or let Chroma generate them with popular embedding models automatically.
- A few lines to RAG — Create a collection, add documents, query by similarity — a working retrieval layer with almost no setup.
- Metadata & full-text filters — Combine vector similarity with metadata and full-text filters in a single query.
- Self-hostable — Run in-process for prototypes or as a self-hosted server under Apache-2.0 — your data stays yours.
The honest read
- Fastest path from zero to a working RAG retrieval layer
- Apache-2.0 licensed and fully self-hostable
- Python and JavaScript clients with the same simple API
- Runs in-process for prototyping, scales to a server in production
- Rust core rewrite for improving performance
- Younger and less battle-tested at massive scale than some peers
- Fewer built-in enterprise features than hosted Pinecone
- Self-hosting at scale needs real infrastructure ops
- Advanced clustering/replication still maturing
FAQ
Yes. Chroma is open source under Apache-2.0 and free to use and self-host. There's also an optional hosted Chroma Cloud if you'd rather not run it yourself.
Storing and querying embeddings for AI apps — semantic search, retrieval-augmented generation (RAG) and long-term memory for LLMs, with metadata and full-text filtering.
Chroma is open source and self-hostable, so your embeddings and documents stay on your own infrastructure, while Pinecone is a closed-source, hosted-only vector database. Chroma also runs in-process for fast local prototyping.
Yes — Chroma runs embedded in your app for prototyping, or as a self-hosted server (with Docker) in production, entirely under your control.
Chroma has official Python and JavaScript/TypeScript clients with the same API, and its core is being rewritten in Rust for performance.
Rust
Python
TypeScript
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