Vearch provides distributed vector search capabilities for applications built around artificial intelligence.
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Chroma provides open-source data infrastructure for AI applications, with vector, full-text, regex, and metadata search.
About Self-host
Chroma provides data infrastructure for retrieval in AI applications. It stores documents, metadata, and embeddings, and supports dense, sparse, and hybrid vector search, full-text and regex search, metadata filtering, and retrieval across text, images, and audio.
It can run locally, be self-hosted, or be used as a managed cloud database, and is accessed through the Chroma SDK. It works with embedding models including OpenAI, Cohere, Hugging Face, and sentence-transformers, with examples for agentic search and code search using AST-aware chunking.
Key features
- Store documents with associated metadata and embeddings
- Dense, sparse, and hybrid similarity search
- Keyword and regex search without embeddings
- Filter search results by metadata conditions
- Index and search text, images, and audio
- Use models from OpenAI, Cohere, Hugging Face, and others
Best for: Developers building AI applications that need retrieval over documents, code, images, and audio.
Good for
- Combines vector, full-text, regex, and metadata search in one system
- Works with multiple embedding providers and models
- Can run locally, be self-hosted, or use a managed cloud database
Self-host at a glance
- Website
- docs.trychroma.com
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Website
- Pricing
- Not confirmed. Check the site
- Platforms
- Web
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Self-host FAQ
Can I run Chroma locally or use a hosted option?
Yes. It is licensed under Apache 2.0 and can run locally, be self-hosted, or use Chroma Cloud.
Do I need to use a specific embedding model?
No. It works with models including OpenAI, Cohere, Hugging Face, and sentence-transformers.
Can I search without embeddings?
Yes. It supports keyword and regex search over data without embeddings.
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