33rd of 8 in Vector databases
Chroma
Embedding database with a four-function API for Python and JavaScript
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- Stars
- 29.5k
- License
- Apache-2.0
- Last commit
- Oct 2026
- Last release
- May 2026
Overview
Chroma is an embedding database with a four-function API (create collection, add, query, get) that tokenizes, embeds and indexes documents itself or accepts your own vectors, with metadata and document filters. It runs in-memory or persisted from the Python or JavaScript client, or as a server via chroma run; the repo ships a Dockerfile and compose file. Chroma Cloud is the hosted serverless version.
Who it is for: developers prototyping RAG who want the simplest API
Strengths
- Four-function API: create collection, add, query, get
- Handles tokenization, embedding and indexing; own vectors optional
- Python and JavaScript clients; chroma run for client-server mode
- Weekly tagged releases on Mondays with hotfixes in between
Weaknesses
- README is thin: no port, resource or auth guidance
- Hosted Chroma Cloud is the headline; self-hosting detail lives in docs
- Row-based API marked coming soon
- No multi-user auth described in the README
What it needs
- no GPU
- Docker + Compose
- Models: built-in embedding or user-supplied vectors
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| #5 | pgvectorPostgreSQL extension for vector similarity search with HNSW and IVFFlat | 59 out of 100 |
| #6 | WeaviateGo vector database with built-in vectorizers, hybrid search and RAG | 57 out of 100 |