# Chroma

> Open-source embedding database — the fast path from prototype to local vector search

**Category:** Memory & Vector  
**Pricing:** open-source  
**Status:** active  
**Tags:** open-source, self-hostable, python  
**Website:** https://trychroma.com  
**Canonical:** https://www.frameworkr.com/tools/chroma

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## What it is

Chroma is an open-source vector store designed to run in-memory or on disk with zero infrastructure setup. It provides a simple Python and TypeScript client, native LangChain and LlamaIndex integrations, and supports metadata filtering. Chroma Cloud offers a managed option for teams ready to move beyond local development.

## Best for

Local development, prototyping, and small-to-medium production deployments where you want full control over your vector store without the cost of a managed service.

## Who it's for

Solo builders and small teams who want to start building immediately without provisioning cloud infrastructure. Zero-cost for self-hosted; Chroma Cloud is paid.

## Agent architecture fit

Chroma fills the same retrieval memory slot in a blueprint as Pinecone — but is the preferred choice during the build phase of any agent. Its in-process mode means zero setup: your agent can start embedding and retrieving without any external service. Migrate to a managed store like Pinecone when the collection grows beyond what local storage can handle or when you need multi-region availability.

## Alternatives

- **Pinecone** — when you need production-grade managed vector search with SLAs, multi-tenancy, or large index sizes
- **Supabase** — when your agent already uses Postgres and you want vector search in the same database


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_Reviewed by Frameworkr — https://www.frameworkr.com/tools/chroma_