# ChromaDB

> Combine vector, text, and metadata search for AI retrieval

ChromaDB is an open-source database and search platform for AI applications. Developers can store documents, embeddings, and metadata, then retrieve relevant records through dense or sparse vector search, full-text search, regular expressions, and metadata filters. These methods can be combined to build retrieval workflows that match both meaning and specific constraints. ChromaDB runs locally through Python, JavaScript, or Docker, with options for in-memory or persistent storage. Chroma Cloud provides a managed deployment path, while dedicated clusters support larger organizational needs. Its shared open-source foundation lets teams prototype locally and move to hosted infrastructure as their search workloads grow.

## Listing details

- Canonical BetaNeon page: https://betaneon.com/products/chromadb
- Official website: https://www.trychroma.com/products/chromadb
- Category: Developer tools / Databases & database tools
- Status: Launched
- Topics: Databases, Open source, Self hosted, Semantic search, Vector search
- Listed: 2026-11-10T12:04:53.914Z
- Content updated: 2026-11-10T12:04:53.999Z
- Official source: https://www.trychroma.com/products/chromadb
This is a product introduction, not an endorsement. Confirm current availability, features, and prices on the official website. Community upvotes on BetaNeon are not star ratings.