Summary
The embedding database that starts as a Python import and grows into a distributed cloud service.
Description
Chroma is the vector store people reach for first, because getting started is genuinely two lines: pip install chromadb, then create a collection. It runs in-process with no server, which makes it ideal for prototypes, notebooks, and tests.
What it does
- In-memory or persistent local storage, so a prototype needs no infrastructure at all
- Automatic embedding using a default model or any provider you configure, so you can pass raw text rather than vectors
- Metadata filtering and full-text search alongside vector similarity
- Multimodal collections for images as well as text
- A client/server mode for when several processes need the same store, and a managed cloud for production scale
Why it matters
Chroma optimised for the first five minutes, and that turned out to be the right call — it is the default in an enormous number of tutorials, courses, and agent frameworks. Crucially, the API is the same locally and in the cloud, so moving from prototype to production is a connection change rather than a rewrite.
Open source under Apache 2.0 and free to self-host; Chroma Cloud is usage-based with a free tier.
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