Chroma
Object-storage-native vector DB, the cheapest at-rest economics in the category
What is Chroma?
Chroma is an Apache 2.0 search infrastructure platform that runs on object storage (S3/GCS) rather than RAM, claiming up to 10x cheaper economics by tiering between hot memory, warm SSD, and cold storage. It supports vector, full-text, regex, and metadata search, with 15M+ monthly downloads and customers including Capital One and UnitedHealthcare. Bought by teams who started on the open-source library and need a hosted version that scales.
Tools for building, hosting, testing, observing, connecting, and giving memory or computer access to AI agents.
See the full Agent Infrastructure guide to compare more tools, buyer criteria, and related workflows.
Use cases to evaluate
Cheap at-rest storage for billions of embeddings rarely queried
RAG prototypes that started in the open-source Python library
Multi-tenant SaaS where most indexes are dormant
Combined vector + full-text + regex search in one store
Fit to evaluate
Developers already using open-source Chroma in production
Cost-sensitive teams with large but cold vector datasets
BYOC buyers who need data in their own VPC
Multi-tenant AI products with thousands of small indexes
Business fit
Right for you if you already use the open-source Chroma library and want a managed cloud, or if your workload is storage-heavy with bursty queries and the S3-backed model fits. Skip if you need sub-10ms p99 on hot indexes at all times, since cold-tier reads will be slower. The $0.33/GiB storage and $0.0075/TiB queried pricing is unusually transparent.
How to evaluate Chroma
Use this category when a business wants agents that do work across tools, APIs, browsers, and data sources.
Confirm the exact workflow
Map Chroma to one concrete workflow first, such as cheap at-rest storage for billions of embeddings rarely queried. Avoid buying before the owner, trigger, output, and success metric are clear.
Check category fit
Compare tool-calling, memory, browser automation, evals, observability, and deployment controls.
Compare practical alternatives
Shortlist Chroma against Orgo, Browser Use, Browserbase so the decision is based on fit, effort, and workflow ownership rather than brand recognition alone.
Validate cost and rollout effort
Starter free ($0/mo + usage, $5 credits, 10 databases). Team $250/mo + usage ($100 credits, 100 databases, SOC II). Usage: writes $2.50/GiB, storage $0.33/GiB-mo, queries $0.0075/TiB queried, network $0.09/GiB. Enterprise is custom. Also confirm implementation time, support needs, and whether the technical setup matches your team.
Compare Chroma with alternatives
Use this quick comparison before booking demos or moving data into a new system.
| Primary workflow | Cheap at-rest storage for billions of embeddings rarely queried, RAG prototypes that started in the open-source Python library |
|---|---|
| Best-fit team | Developers already using open-source Chroma in production, Cost-sensitive teams with large but cold vector datasets |
| Implementation effort | Technical setup and maintenance profile |
| Pricing check | Free plan + paid plans |
| Closest alternatives | OrgoBrowser UseBrowserbaseHyperbrowser |
Chroma pricing
| Model | Free plan + paid plans |
|---|---|
| Snapshot | Starter free ($0/mo + usage, $5 credits, 10 databases). Team $250/mo + usage ($100 credits, 100 databases, SOC II). Usage: writes $2.50/GiB, storage $0.33/GiB-mo, queries $0.0075/TiB queried, network $0.09/GiB. Enterprise is custom. |
| Checked |
Common questions about Chroma
What is Chroma?
Chroma is an Apache 2.0 search infrastructure platform that runs on object storage (S3/GCS) rather than RAM, claiming up to 10x cheaper economics by tiering between hot memory, warm SSD, and cold storage. It supports vector, full-text, regex, and metadata search, with 15M+ monthly downloads and customers including Capital One and UnitedHealthcare. Bought by teams who started on the open-source library and need a hosted version that scales.
What is Chroma used for?
Common use cases: Cheap at-rest storage for billions of embeddings rarely queried; RAG prototypes that started in the open-source Python library; Multi-tenant SaaS where most indexes are dormant; Combined vector + full-text + regex search in one store.
How much does Chroma cost?
Starter free ($0/mo + usage, $5 credits, 10 databases). Team $250/mo + usage ($100 credits, 100 databases, SOC II). Usage: writes $2.50/GiB, storage $0.33/GiB-mo, queries $0.0075/TiB queried, network $0.09/GiB. Enterprise is custom.
Who is Chroma best for?
Chroma fits Developers already using open-source Chroma in production, Cost-sensitive teams with large but cold vector datasets, BYOC buyers who need data in their own VPC, Multi-tenant AI products with thousands of small indexes. Right for you if you already use the open-source Chroma library and want a managed cloud, or if your workload is storage-heavy with bursty queries and the S3-backed model fits. Skip if you need sub-10ms p99 on hot indexes at all times, since cold-tier reads will be slower. The $0.33/GiB storage and $0.0075/TiB queried pricing is unusually transparent.
What are alternatives to Chroma?
Common alternatives to Chroma include Orgo, Browser Use, Browserbase, Hyperbrowser, Steel, Anchor Browser.