Chroma
About Chroma
Chroma offers open-source search infrastructure for AI. The product provides serverless infrastructure supporting vector, full-text, regex, and metadata search. It is built on object storage. It is licensed under Apache 2.0.
Used for
- Performing dataset versioning, A/B testing, and roll-outs via forking.
- Filtering and faceting search results by metadata.
- Running trigram and regex searches over text.
- Monitoring real-time indexing progress of collections.
Who it is for
- The product is used by developers.
- It is used in open-source codebases on GitHub.
From Chroma's own website, read 2026-10-23. How we build listings.
How to evaluate Vector Databases & RAG
This is how the CIOPages Research Team evaluates this category. It is not an assessment of Chroma. It comes from our Vector Database & AI Search buyer guide.
25%
Retrieval Quality & Index Options
ANN algorithms offered (HNSW, IVF/IVF-PQ, DiskANN, GPU/CAGRA), achievable recall@k at your latency budget, quantization for memory savings, and whether the index supports real-time inserts or needs rebuilds
20%
Hybrid Search & Filtering at Scale
Native vector+keyword (BM25 / sparse) fusion, reranking, and — critically — in-graph metadata pre-filtering that holds recall under selective filters rather than degrading to brute force or empty result sets
20%
Scale, Performance & Freshness
Vector ceiling per node and horizontally, p95/p99 latency and QPS under your real filters, multi-tenancy and namespaces, multi-region, and how fast new or updated embeddings become queryable (insert-to-searchable lag)
15%
Operating Model & Lock-In
Managed SaaS vs. self-hosted vs. bring-your-own-cloud, license terms (Apache 2.0 / BSD vs. proprietary), data-export and migration path, and how much sync/ETL you take on if vectors live apart from the source data
10%
Security, Governance & Residency
RBAC and API-key scoping, encryption in transit and at rest, SOC 2 / ISO 27001 / GDPR posture, data residency and VPC/air-gapped options, and inherited governance (e.g. Unity Catalog, platform IAM) where applicable
10%
Developer Experience & Ecosystem
Client SDKs and API ergonomics, LangChain / LlamaIndex / framework integrations, built-in or hosted embedding and reranking, docs quality, and operational maturity (backups, observability, upgrades)
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Quick Facts
www.trychroma.com Pricing pageCategoryAI & ML Platforms
SubcategoryVector Databases & RAG
PricingUsage-based
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