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Chroma

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Spec score 9.4 #1 of 40 in Ai Databases

What it is

Chroma is open-source infrastructure for storing embeddings and metadata, then searching and retrieving information across text, images, and other modalities. Search options include dense, sparse, and hybrid vector search, plus full-text and regex search and metadata filtering. It can run locally through pip, npm, or Docker, on Chroma Cloud, or in a customer’s own VPC. The maker says its Apache 2.0-licensed codebase powers both the open-source database and Chroma Cloud. Documented integrations include embedding providers such as OpenAI, Cohere, Google Gemini, Hugging Face, Jina AI, and Ollama, and frameworks such as LangChain, LlamaIndex, Haystack, Streamlit, and DeepEval. Cloud security features include encryption in transit and at rest, SSO, role-based access control, and employee MFA; Chroma Cloud has completed a SOC 2 Type II examination. Starter is free, with 10 databases and 10 team members. Team is $250 a month plus usage and includes $100 credits, 100 databases, and 30 team members.

Spec sheet

What it does
ChromaDB is open-source search infrastructure for AI applications, combining vector, full-text, regex, and metadata search.Read 15 Oct 2026 · trychroma.com
Purpose
Chroma is open-source data infrastructure for AI that stores embeddings and metadata and supports search and retrieval across text, images, and other modalities.Read 28 Sep 2026 · docs.trychroma.com
Deployment
The maker says Chroma can run locally with pip, npm, or Docker, on Chroma Cloud, or in a customer’s own VPC.Read 28 Sep 2026 · trychroma.com
Free plan
YesRead 22 Sep 2026 · trychroma.com
Paid from
250Read 22 Sep 2026 · trychroma.com
Security
Chroma Cloud says customer data is encrypted in transit and at rest and that access controls include SSO, role-based access control, and employee MFA.Read 28 Sep 2026 · trychroma.com
Compliance
Chroma Cloud says it completed a SOC 2 Type II examination.Read 28 Sep 2026 · trychroma.com
Support
The pricing page lists Community Slack for Starter, Slack support for Team, and dedicated support for Enterprise.Read 28 Sep 2026 · trychroma.com
Changelog update
The changelog lists EU region support in April 2026 and Chroma Sync for S3, GitHub and Web in March 2026.Read 15 Oct 2026 · trychroma.com
CLI installation
The CLI is installable through the Python package, JavaScript package, pipx or a standalone curl installer.Read 15 Oct 2026 · docs.trychroma.com
Cloud API
The CloudClient accepts a tenant, database and API key, with environment-variable configuration also supported.Read 15 Oct 2026 · docs.trychroma.com
Cloud architecture
Chroma Cloud is serverless and uses object storage with automatic tiering and caching.Read 15 Oct 2026 · docs.trychroma.com
Cloud performance limits
The product page lists 1 million collections per database and 5 million records per collection as technical specifications.Read 28 Sep 2026 · trychroma.com
Company founding
Netfigo lists Chroma as founded in 2022 in San Francisco, with Jeff Huber and Anton Troynikov as founders.Read 15 Oct 2026 · netfigo.com
Company legal name
The terms identify the service provider as Chroma Inc.Read 15 Oct 2026 · trychroma.com
Company location and size
LinkedIn lists Chroma as privately held, headquartered in San Francisco and employing 11–50 people.Read 15 Oct 2026 · linkedin.com
Dataset forking
Forking supports dataset versioning, A/B tests and staged rollouts.Read 15 Oct 2026 · trychroma.com
Documentation depth
The docs cover quickstarts, SDK references, cloud clients, deployment, Docker, production client-server mode, performance and migrations.Read 15 Oct 2026 · docs.trychroma.com
Embedding integrations
Documented embedding integrations include OpenAI, Cohere, Google Gemini, Hugging Face, Jina AI, Ollama, and others.Read 28 Sep 2026 · docs.trychroma.com
Enterprise deployment
Enterprise deployment options listed include multi-tenant cloud, single-tenant nodes and clusters, BYOC, and on-premises deployment.Read 28 Sep 2026 · trychroma.com
Enterprise options
The enterprise page lists single-region, multi-region, and multi-cloud regions, active-active and active-passive replication, and AWS, GCP, and Azure.Read 28 Sep 2026 · trychroma.com
Framework integrations
Documented framework integrations include LangChain, LlamaIndex, Haystack, Streamlit, and DeepEval.Read 28 Sep 2026 · docs.trychroma.com
Full-text and regex
Its search interface includes trigram full-text matching and regular-expression queries.Read 15 Oct 2026 · trychroma.com
Funding news
Chroma announced an $18 million seed round led by Quiet Capital on April 7, 2023, and also disclosed a May 2022 pre-seed round.Read 15 Oct 2026 · trychroma.com
Integrations: embedding providers
Documented embedding integrations include OpenAI, Google Gemini, Cohere, Hugging Face, Jina AI, Ollama, Mistral and Together AI.Read 15 Oct 2026 · docs.trychroma.com
Integrations: frameworks
Documented framework integrations include LangChain, LlamaIndex, DeepEval, Streamlit, Haystack, Google ADK, Mem0 and others.Read 15 Oct 2026 · docs.trychroma.com
Licence
Chroma is released under the Apache 2.0 licence.Read 15 Oct 2026 · trychroma.com
Limit: comparison performance
A G2 reviewer says performance can fall below Pinecone in some scenarios.Read 15 Oct 2026 · g2.com
Limit: documentation and learning curve
A G2 reviewer cites limited advanced documentation, a potentially steep beginner learning curve and a focus narrower than general databases.Read 15 Oct 2026 · g2.com
Limit: LangChain integration and visibility
A G2 reviewer reports occasional LangChain integration trouble and says indexes are less visible than in FAISS.Read 15 Oct 2026 · g2.com
Limit: narrow use cases
A G2 reviewer says Chroma has limited use cases compared with more general databases.Read 15 Oct 2026 · g2.com
Limit: production readiness
A G2 reviewer reports a memory leak and considers the product insufficiently production-ready.Read 15 Oct 2026 · g2.com
Limit: similarity scores
A G2 reviewer reports bugs where similarity-score parameters may produce inaccurate scores.Read 15 Oct 2026 · g2.com
Metadata search
Metadata conditions can be used for filtering and faceted retrieval.Read 15 Oct 2026 · trychroma.com
Migration limitation
The migration guide says built-in authentication implementations were removed in the v1.0.0 changes.Read 15 Oct 2026 · docs.trychroma.com
Multimodal retrieval
The documentation describes indexing and retrieving text, images, audio and other modalities.Read 15 Oct 2026 · docs.trychroma.com
Open source
Chroma is licensed under Apache 2.0, and the maker says the same codebase powers its open-source database and Chroma Cloud.Read 28 Sep 2026 · trychroma.com
Open-source adoption
The public GitHub repository showed about 29,500 stars and 2,600 forks when opened.Read 15 Oct 2026 · github.com
Praise: ease of use
G2 reviewers praise easy setup, straightforward embedding storage and simple similarity-search or RAG workflows.Read 15 Oct 2026 · g2.com
Praise: performance and deployment
G2 reviewers describe the database as highly optimized, high performance and easy to deploy in cloud environments.Read 15 Oct 2026 · g2.com
Published performance
The product page lists 20 ms warm p50 latency and 650 ms cold p50 latency at 384 dimensions and 100,000 vectors.Read 15 Oct 2026 · trychroma.com
Published scale limits
Listed technical specifications include 30 MB/s write throughput per collection, 10 concurrent reads, 1 million collections per database and 5 million records per collection.Read 15 Oct 2026 · trychroma.com
Rating on G2
4.2 out of 5 from 6 reviews.Read 15 Oct 2026 · g2.com
SDKs
Official documentation provides Python, TypeScript and Rust client examples and references.Read 15 Oct 2026 · docs.trychroma.com
Search
Chroma supports dense, sparse, and hybrid vector search, full-text and regex search, and metadata filtering.Read 28 Sep 2026 · docs.trychroma.com
Security certification
Chroma Cloud says it has completed an independent SOC 2 Type II examination.Read 15 Oct 2026 · trychroma.com
Security controls
The security page states that customer data is encrypted in transit and at rest, employee production access requires MFA, and AWS GuardDuty and Inspector are used for threat detection.Read 15 Oct 2026 · trychroma.com
Self-hosting
A Chroma server can run locally or in Docker and can be deployed on AWS, GCP, Azure and other cloud providers.Read 15 Oct 2026 · docs.trychroma.com
Sparse search
Chroma provides lexical sparse search methods including BM25 and SPLADE.Read 15 Oct 2026 · trychroma.com
Usage limits
The pricing FAQ says exceeding customer-set or Chroma-set usage limits pauses the service until the limit is changed.Read 28 Sep 2026 · trychroma.com
Vector search
The product supports semantic similarity search over dense vector embeddings.Read 15 Oct 2026 · trychroma.com

Plans and prices

Starter Free Free credits then usage-based pricing 10 databases · 10 team members Read 22 Sep 2026 · trychroma.com
Team $250 a month $250/month + usage 100 databases · 30 team members · $100 usage credits · Slack support · SOC 2 · volume discounts Read 15 Oct 2026 · trychroma.com
Starter Free $0/month + usage 10 databases · 10 team members · Community Slack Read 15 Oct 2026 · trychroma.com
Enterprise Priced on request Custom pricing Unlimited databases · Unlimited team members · Dedicated support · Single-tenant clusters · BYOC clusters · SLAs Read 15 Oct 2026 · trychroma.com

Every Chroma plan and price →

Strong points and limits

Strong points

  • Supports dense, sparse, and hybrid vector search.
  • Offers full-text, regex, and metadata search.
  • Runs locally, in cloud, or in a customer VPC.
  • Apache 2.0 license and documented framework integrations.

Limits

  • Team starts at $250 a month plus usage.
  • Usage-limit overages pause the service.

Who it suits

Chroma suits teams building AI applications that need vector search, metadata filtering, or integrations with embedding and application frameworks. Its local, cloud, VPC, and enterprise deployment options accommodate different operating setups.

Chroma in depth

Read the full write-up

Overview

Chroma is open-source infrastructure for storing embeddings and metadata and retrieving information across text, images, and other modalities. It suits developers building AI applications who want several search methods and a choice of local, hosted, or customer-controlled deployment. Its flexibility is a strength, but cloud buyers should weigh usage pauses and plan caps before committing.

Key features

Broad retrieval: Dense, sparse, and hybrid vector search combine with full-text and regex search, plus metadata filtering. That range suits applications that need more than nearest-neighbor retrieval; teams with a narrow vector-search requirement may not need the additional modes.

Index and dimension options: Chroma supports vector and sparse-vector indexes, full-text indexing, and inverted indexes for strings, integers, floats, and booleans. The maximum dimension count is 4096, a meaningful ceiling to check against the embeddings an application will use.

Developer integrations: Documented embedding integrations include OpenAI, Cohere, Google Gemini, Hugging Face, Jina AI, and Ollama. Framework integrations include LangChain, LlamaIndex, Haystack, Streamlit, and DeepEval; SDKs cover Python, TypeScript, Rust, Kotlin, and Swift. This breadth gives teams several ways to fit Chroma into an existing AI stack.

Deployment choice: The Apache 2.0-licensed database runs locally through pip, npm, or Docker, on Chroma Cloud, or in a customer’s own VPC. The maker says the same codebase powers the open-source database and Chroma Cloud, which helps teams move between self-managed and hosted use without choosing a separate product.

Cloud controls: Chroma Cloud encrypts customer data in transit and at rest, and provides SSO, role-based access control, and employee MFA. Chroma says it completed a SOC 2 Type II examination. Enterprise deployment options include multi-tenant cloud, single-tenant nodes and clusters, BYOC, and on-premises deployment, with single- or multi-region and multi-cloud options across AWS, GCP, and Azure.

Cloud capacity and limits: Technical specifications list up to 1 million collections per database and 5 million records per collection. Separately, exceeding customer-set or Chroma-set usage limits pauses service until the limit changes. That pause behavior matters for production workloads that cannot tolerate interruptions.

Pricing

Starter: Free, with 10 databases and 10 team members. It includes free credits, then switches to usage-based pricing. This is the sensible starting point for evaluation or a small deployment, but the database and seat caps constrain larger teams, and usage after credits is not a fixed-cost arrangement. Starter includes Community Slack support.

Team: $250 a month, plus usage, with $100 credits, 100 databases, and 30 team members. It adds Slack support, SOC II, and volume-based discounts. This fits teams needing more capacity and support than Starter, but the base price is not the whole bill: usage is extra, and exceeding usage limits pauses service until they are changed.

Enterprise: Custom pricing, with unlimited databases and team members and dedicated support. It is the fit for organizations needing uncapped account-level database and seat counts alongside the listed enterprise deployment choices. The plan price is custom, so teams should assess it against their deployment and support needs.

Platforms

Chroma supports Android, iOS, Linux, macOS, Windows, web, API, and self-hosted use. Its local installation paths and VPC, cloud, and on-premises options give teams more deployment control than a cloud-only service.

Who it's for

Chroma is best suited to AI developers and organizations that want flexible retrieval, broad embedding and framework integrations, and the option to start locally before adopting managed cloud or enterprise deployment. It is less suitable for buyers who need predictable cloud spending without usage-based charges or cannot accept service pauses when limits are exceeded.

Pros and cons

Pro: Dense, sparse, hybrid, full-text, regex, and metadata search support varied retrieval patterns in one system.

Pro: Apache 2.0 licensing and local, cloud, VPC, and on-premises deployment give teams meaningful control over where the database runs.

Pro: A broad set of embedding, framework, and language integrations lowers the friction of fitting Chroma into varied AI stacks.

Con: Starter is capped at 10 databases and 10 team members; Team raises those caps but costs $250 a month plus usage.

Con: Usage-limit breaches pause service until limits change, a material operational risk for workloads that need uninterrupted retrieval.

Alternatives

Vespa is worth considering if a paid, resource-priced option is preferable: its Startup plan charges by vCPU, memory, disk, and GPU memory, and it offers a free trial but no free plan.

Qdrant is a close alternative for teams seeking a free cloud entry point: its Free Tier is free forever and includes a single-node cluster with 0.5 vCPU, 1 GB RAM, and 4 GB disk.

Pinecone may suit teams comparing a hosted API-and-web option with a free plan and trial; its Starter plan includes stated index, namespace, storage, and monthly read/write-unit caps.

Zvec is an alternative open-source, Apache 2.0 in-process vector database with a free plan.

Actian Zen is another option to consider.

Upstash Vector may fit teams that want a free hosted tier with explicit daily query and update limits, plus a pay-as-you-go plan.

Zilliz Cloud offers a free cluster capped at 5 GB storage and 5 collections, a useful alternative for evaluating a hosted service within those limits.

KDB.AI is another alternative to compare.

For a broader shortlist, browse Vector Databases, Search Databases, Embedded Databases, and Database Software.

Verdict

Choose Chroma if your AI application needs several retrieval modes, broad integrations, and the freedom to run locally, in the cloud, or in your own environment. Its main advantage is that range; its main drawback for cloud buyers is usage-based billing combined with service pauses at exceeded limits. For workloads that depend on uninterrupted service or require tightly predictable costs, compare alternatives before choosing a cloud plan.

Verdict

Chroma combines multiple search methods with broad embedding and framework integrations. Check the usage-limit behavior and plan terms against your workload before choosing a cloud plan.

Where Specifiction places it

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