Chroma
Store document embeddings and query matching records for AI applications.
Overview
What you provide
- Documents or embeddings, stable IDs and metadata filters
What you get
- Matching records with IDs, metadata and distances
Setup & workflow
- Install chromadb and create a collection locally, or configure a separate server.
- Prepare the input: Documents or embeddings, stable IDs and metadata filters.
- Run a small, reversible example and inspect the output: Matching records with IDs, metadata and distances.
- Use known queries to check retrieval relevance, filtering and persistence.
Requirements & installation
- Configure the documented runtime and authorized service access before attempting this workflow.
Limits & review
- A vector database returns retrieval results, not a finished research report.
- Evidence review only: the product was not installed or tested in this crawl.
Your part
- Use known queries to check retrieval relevance, filtering and persistence.
When to consider another product
Unreviewed production decisions, unrestricted account access or guaranteed factual results.
Plans & billing details
Cost planning
- Review scope is licensing and documented free-use boundaries, not numeric prices or current hosted-plan allowances.
Published prices are a snapshot. Confirm billing cycle, taxes and current allowances with the provider.
Sources & verification3
This profile is based on official sources, not a hands-on product test.
Vendor descriptions and demos document advertised features. Editorial guidance is based on these sources.
Discovered via OpenFree.Tools.
- Chroma — official READMEraw.githubusercontent.com
The maintainer README supports this scope: Store document embeddings and query matching records for AI applications.
- Chroma — product entry pointwww.trychroma.com
The public product entry point was retrieved. Functional scope and setup in this record are grounded in the linked maintainer README.
- Chroma — license termsraw.githubusercontent.com
The retrieved license materials support this boundary: Apache-2.0. Review the complete terms for your use case.
Frequently asked questions
What does Chroma do?
Store document embeddings and query matching records for AI applications.
How much does Chroma cost?
Software or published weights are available under Apache-2.0. Model inference, external services and your own compute are separate; hosted plan prices were not reviewed.
What should I check before using Chroma?
A vector database returns retrieval results, not a finished research report.