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Chroma Review 2026 — Best Open-Source Vector Database for AI
Chroma is the easiest open-source vector database for RAG. Add semantic search in 3 lines of Python. Native LangChain/LlamaIndex integration. Free, Apache 2.0 license.
Chroma provides document storage, embeddings, dense and sparse vector search, full-text and regex search, metadata filtering, and multimodal retrieval. Developers can run it locally, self-host it, or use Chroma Cloud as a managed database.
It is used for retrieval-augmented generation, agentic search, code search, and dataset versioning. Chroma Cloud has a free Starter plan, while paid plans and usage charges apply for larger deployments and enterprise features.
Features
- Dense, sparse, and hybrid vector search
- Full-text, keyword, trigram, and regex search
- Metadata filtering and faceted search
- Store documents, embeddings, and metadata
- Multimodal retrieval for text, images, and audio
- Collection forking for dataset versioning and A/B testing
- Command-line tools for development
- Apache 2.0 open-source license
Use cases
- Build retrieval-augmented generation systems
- Create agents that search and refine results
- Index codebases for coding-agent search
- Version datasets and test search roll-outs
- Search documents, images, audio, and metadata together
Pros
Cons
Pricing
- Starting price
- $250/month
- Pricing checked
- 2026-09-19
Starter
$0/month
- $0 + usage
- 10 databases
- 10 team members
- Community Slack
- $5 in free credits
Team
$250/month
- $250 + usage
- 100 databases
- 30 team members
- Slack support
- SOC II
- Volume-based discounts
Enterprise
Custom
- Unlimited databases
- Unlimited team members
- Dedicated support
- Single tenant clusters
- BYOC clusters
- SLAs