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chroma

separate

Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.

When to use

• Building RAG (retrieval-augmented generation) applications
• Need local/self-hosted vector database
• Want open-source solution (Apache 2.0)
• Prototyping in notebooks
• Semantic search over documents
• Storing embeddings with metadata
• **24,300+ GitHub stars**
• **1,900+ forks**

When not to use

• Managed cloud auto-scaling
• Pure similarity search without metadata
• Production ML-native database
• High performance Rust-based systems

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