[metadata]
description: Open-source search infrastructure for AI
og:description: Open-source search infrastructure for AI
og:image: https://www.trychroma.com/card.png
og:image:height: 1256
og:image:width: 2400
og:locale: en_US
og:site_name: Chroma
og:title: Chroma - open-source search infrastructure for AI
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og:url: https://www.trychroma.com
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theme-color: #fafaf9
twitter:card: summary_large_image
twitter:creator: @trychroma
twitter:creator:id: 1507488634458439685
twitter:description: Open-source search infrastructure for AI
twitter:image: https://www.trychroma.com/card.png
twitter:site: trychroma
twitter:site:id: 1507488634458439685
twitter:title: Chroma - open-source search infrastructure for AI
viewport: width=device-width, initial-scale=1

[document-links]
/home
27k: https://github.com/chroma-core/chroma
70% Data Throughput Increase Performance boost using base64 vector encoding. Jul 2025: /changelog/base64-data-throughput
About: https://docs.trychroma.com/docs/overview/introduction
Agent: /products/agent
All plans →: /pricing
Beyond The Embedding: Vector Indexing 11:26: https://youtu.be/1QdwYWd3S1g
Careers: /careers
Changelog: /changelog
Chroma Cloud Sync Serverless data ingestion for Chroma Cloud. Mar 2026: /changelog/chroma-sync-s3-github-and-web
Chroma Context-1 13:20: https://www.youtube.com/watch?v=4sAJLLWPAh4
Chroma Web Sync Automatically crawl, scrape, chunk and embed web pages. Nov 2025: /changelog/chroma-web-sync
Chunking Strategies Evaluating chunking strategies in retrieval for AI.: /research/evaluating-chunking
Collection Forking Fast duplication of collections with copy-on-write. Aug 2025: /changelog/forking
Contact us: /talk-with-us
Contact: mailto:hello@trychroma.com
Context Engineering Episode 3 - Lance Martin - LangChain 1:02:36: https://www.youtube.com/watch?v=MJScoDgIcXg
Context Engineering for Engineers 11:16: https://youtu.be/L8ZM78APDPk
Context Engineering with DSPy 12:46: https://youtu.be/1I9PoXzvWcs
Context Engineering: The Outer Loop 23:43: https://youtu.be/vsfbplnJyA8
Context Rot 7:55: https://youtu.be/TUjQuC4ugak
Context Rot How increasing input tokens impacts LLM performance.: /research/context-rot
Context-1 Training a self-editing search agent.: /research/context-1
Customer-Managed Encryption Keys Encrypt your data with your own encryption keys. Dec 2025: /changelog/cmek
DPA: /dpa
Database: /products/chromadb
Deep dive: Using Reranking to improve search results 15:23: https://www.youtube.com/watch?v=FHXRWwpQYY8
Designing a query execution engine A push-based, morsel-driven execution engine in Rust. Aug 2025: engineering/execution-engine
Discord →: https://discord.gg/MMeYNTmh3x
Discord: https://discord.gg/MMeYNTmh3x
Docs: https://docs.trychroma.com
Docs: https://docs.trychroma.com/
Embedding Adapters Lightweight transforms to boost embedding accuracy.: /research/embedding-adapters
Enterprise plan →: /enterprise
Enterprise: /enterprise
Generative Benchmarking New methods for evaluating retrieval systems.: /research/generative-benchmarking
GitHub: https://github.com/chroma-core/chroma
Github →: https://github.com/chroma-core/chroma
GroupBy Group and aggregate search results by metadata keys. Jan 2026: /changelog/groupby
Indexing Status Monitor real-time indexing progress of your collections. Jan 2026: /changelog/indexingstatus
Introducing Chroma Cloud Chroma Cloud is now generally available. Aug 2025: /changelog/introducing-chroma-cloud
Introducing Chroma Sync Automatically chunk, embed, and index GitHub repos. Oct 2025: /changelog/introducing-chroma-sync
JavaScript / TypeScript getting started docs →: https://docs.trychroma.com/docs/overview/getting-started#typescript
JavaScript Client V3 Complete rewrite with reduced bundle size. Jun 2025: /changelog/js-client-v3
Learn more: /enterprise
Lexical Search in Chroma 4:41: https://www.youtube.com/watch?v=XHEgXDff2xw
Long live Context Engineering 57:00: https://www.youtube.com/watch?v=pIbIZ_Bxl_g
Metadata Arrays Store arrays of strings, numbers, and booleans in metadata. Feb 2026: /changelog/metadata-arrays
Open-source →: https://discord.gg/MMeYNTmh3x
Package Search MCP Query thousands of open-source repos through MCP. Sep 2025: /changelog/package-search-mcp
Package Search MCP: /package-search
Pricing: /pricing
Privacy: /website-privacy
Private Networking Secure connectivity with AWS PrivateLink support. Jan 2026: /changelog/private-networking
Pro plan →: /pricing
Python getting started docs →: https://docs.trychroma.com/docs/overview/getting-started
Read Level Control read consistency with index-only or full read modes. Jan 2026: /changelog/readlevel
Read case study →: /customers/mintlify-case-study
Read case study →: /customers/propel-ai-case-study
Read the docs: https://docs.trychroma.com/
Regex Search Support Search using regular expressions with new operators. Jun 2025: /changelog/regex
Reliability at Scale 26:30: https://youtu.be/XVFevYxRKAE
Research: /research
Run Chroma OSS →: https://docs.trychroma.com/deployment
Schema() and Search() APIs 9:02: https://www.youtube.com/watch?v=EtUjXsowN_4
Security: /security
See more Visit our YouTube channel →: https://youtube.com/@trychroma
See open roles: /careers
Social →: https://twitter.com/trychroma
Sparse Vector Search First class support for BM25 and SPLADE vectors. Oct 2025: project/sparse-vector-search
Status: https://status.trychroma.com
Sync: /products/sync
Terms: /website-terms
Updates: /updates
Use cases: /updates/customers
Videos: https://www.youtube.com/@trychroma
View full documentation →: https://docs.trychroma.com/docs/overview/introduction
X: https://x.com/trychroma
YouTube.: https://www.youtube.com/@trychroma
YouTube: https://www.youtube.com/@trychroma
get started locally: https://docs.trychroma.com/docs/overview/getting-started
wal3: Chroma's Write-Ahead Log A Write-Ahead Log for Chroma, Built on Object Storage Sep 2025: engineering/wal3

[content]
Chroma - open-source search infrastructure for AI
Products
Products
Sync
Database
Agent
Docs
Research
Resources
Resources
Use cases
Updates
Videos
Changelog
Discord
GitHub
Support
Hidden
Pricing
27k
Log in
Sign up
Open-source search infrastructure for AI
Fast, serverless, and scalable infrastructure supporting vector, full-text, regex, and metadata search. Built on object storage and trusted by millions of developers. Open-source Apache 2.0.
Start free on Cloud
Read the docs
Or,
get started locally
.
Read case study →
Read case study →
Agent
Search
AI App
Ask a question
What can I build with Chroma?
Who else uses Chroma?
How does Chroma scale?
knowledge_base
Chroma
knowledge_base -
1,277,467
records
awaiting query input
15M+
monthly downloads
Apache 2.0
27k Github stars
Low latency
search
Fast queries over billions of multi-tenant indexes.
Up to
10x
cheaper
Built on object storage with automatic data tiering.
No
engineering ops
Scales with your data and traffic. SOC 2 Type II.
Features
◇
Sparse vector search
Lexical search (BM25, SPLADE)
◆
Vector search
Semantic similarity search
●
Full-text search
Trigram and regex search
◐
Metadata search
Filtering and faceted search
◊
Forking
Dataset versioning, A/B testing, and roll-outs
▣
CLI
Command-line tools for development
TypeScript
Python
Rust
Copy
// configure client and collection for sparse embeddings (BM25, SPLADE)
// Add documents with sparse embeddings (BM25)
await
collection.
add
({
ids: [
"id1"
,
"id2"
],
documents: [
"Document about databases"
,
"ML tutorial"
]
})
// Query with sparse vector
const
sparseRank
=
Knn
({ query:
"ML"
, key:
"sparse_embedding"
});
// Build and execute search
const
search
=
new
Search
()
.
rank
(sparseRank)
.
limit
(
10
)
.
select
(
K
.
DOCUMENT
,
K
.
SCORE
);
const
results
=
await
collection.
search
(search);
Terminal Output
$ node sparse-search.js Connecting to Chroma... ✓ Connected successfully Creating collection 'my_collection'... ✓ Collection created Adding documents with sparse embeddings (BM25)... ✓ Added 2 documents Querying with sparse vector... ✓ Query completed in 18ms Results (ranked by BM25 score): [ { id: "id1", document: "Document about databases", score: 0.87, metadata: {} }, { id: "id2", document: "ML tutorial", score: 0.45, metadata: {} } ]
Performance
Fast search over billions of multi-tenant indexes
Chroma's indexes are built and optimized for object-storage offering unparalleled cost and performance. State-of-the-art vector, full-text, and regex search.
Latency
Query Latency
@384 dim at 100k vectors
Warm
Cold
p50
20ms
650ms
p90
27ms
1.2s
p99
57ms
1.5s
Contact us
to run a POC for your specific workload.
Dedicated clusters can be scaled to your specific requirements.
Technical specs
Write throughput (per collection)
30 MB/s (2000+ QPS)
Concurrent reads (per collection)
10 (200+ QPS)
Collections per database
1M
Records per collection
5M
Recall
90-100%
Zero-ops infra
┌───────────────────────────────┐ │ Query Layer │ │ Fast memory cache (hot) │ │ SSD cache (warm) │ └───────────────────────────────┘ ↕ Intelligent tiering ┌───────────────────────────────┐ │ Storage Layer │ │ S3 / GCS (cold) │ │ • All vectors │ │ • All metadata │ │ • All indexes │ └───────────────────────────────┘
Unlike legacy search systems, Chroma is a database you'll want to be on-call for.
✓
Auto-scales with usage
✓
No manual tuning
✓
Serverless pricing
Chroma takes full advantage of object storage with automatic query-aware data tiering and caching.
✓
Vectors are large: 1GB text → 15GB of vectors
✓
Memory is expensive: $5/GB/mo
✓
Object storage is not: $0.02/GB/mo
Enterprise
Chroma brings the security, compliance, education and operational model enterprises need with our Apache 2.0 architecture.
BYOC in your VPC, multi-cloud/multi-region replication, point-in-time-recovery ensure a resilient and scalable search system with the same 0-ops story as Cloud.
Learn more
Contact us
Hidden
▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓ ▓░ ░▓ ▓░ ┌──────────── YOUR VPC ─────────────┐ ░▓ ▓░ │ │ ░▓ ▓░ │
█ DATA PLANE █
│ ░▓ ▓░ │ │ ░▓ ▓░ │ Your data, your cloud │ ░▓ ▓░ │ │ ░▓ ▓░ │ │ ░▓ ▓░ └───────────────────────────────────┘ ░▓ ▓░
│
░▓ ▓░
│
░▓ ▓░
▼
░▓ ▓░
═════════════════════════════════════
░▓ ▓░
░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
░▓ ▓░ ░▓ ▓░ ┌────────── CHROMA VPC ─────────────┐ ░▓ ▓░ │ │ ░▓ ▓░ │
█ CONTROL PLANE █
│ ░▓ ▓░ │ │ ░▓ ▓░ │ Managed by Chroma │ ░▓ ▓░ │ Monitoring, backups, ops │ ░▓ ▓░ │ │ ░▓ ▓░ └───────────────────────────────────┘ ░▓ ▓░ ░▓ ▓░ ✓ BYOC in your VPC ░▓ ▓░ ✓ Multi-region replication ░▓ ▓░ ✓ 0-ops management ░▓ ▓░ ░▓ ▓░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░▓ ▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒
[▶] Videos
Deep dive: Using Reranking to improve search results
15:23
Chroma Context-1
13:20
Lexical Search in Chroma
4:41
Schema() and Search() APIs
9:02
Context Engineering Episode 3 - Lance Martin - LangChain
1:02:36
Beyond The Embedding: Vector Indexing
11:26
Long live Context Engineering
57:00
Context Rot
7:55
Context Engineering: The Outer Loop
23:43
Context Engineering for Engineers
11:16
Reliability at Scale
26:30
Context Engineering with DSPy
12:46
See more
Visit our YouTube channel →
[●] Open source community
Open-source databases give your team the control and flexibility to build exactly what you need. No licensing limits, no vendor lock-in, just reliable performance backed by a large community.
Github →
Chroma has over 26k GitHub stars and is used in over 90k other open-source codebases on GitHub. It is downloaded over 11M times a month.
Discord →
Join the Discord to see what people are building!
Social →
Find the greater community on
X
and
YouTube.
Run Chroma OSS →
Run Chroma on your own infrastructure with our open-source deployment guides.
[◆] Support
Open-source →
Join our 10K person strong Discord community to get fast and expert help from the open-source community.
All plans →
Helpful support direct from engineers on the Chroma team
Pro plan →
Direct Slack communication for fast support and help designing and iterating your search system.
Enterprise plan →
Customized SLAs ensure your team gets 24/7 assistance.
[▲] Research
Our research spans both basic and applied research for search, retrieval, agents, and context engineering.
Context-1
Training a self-editing search agent.
Context Rot
How increasing input tokens impacts LLM performance.
Generative Benchmarking
New methods for evaluating retrieval systems.
Chunking Strategies
Evaluating chunking strategies in retrieval for AI.
Embedding Adapters
Lightweight transforms to boost embedding accuracy.
[■] Updates
Chroma's project is rapidly improving. Here are the latest updates.
Chroma Cloud Sync
Serverless data ingestion for Chroma Cloud.
Mar 2026
Metadata Arrays
Store arrays of strings, numbers, and booleans in metadata.
Feb 2026
Indexing Status
Monitor real-time indexing progress of your collections.
Jan 2026
Read Level
Control read consistency with index-only or full read modes.
Jan 2026
Private Networking
Secure connectivity with AWS PrivateLink support.
Jan 2026
GroupBy
Group and aggregate search results by metadata keys.
Jan 2026
Customer-Managed Encryption Keys
Encrypt your data with your own encryption keys.
Dec 2025
Chroma Web Sync
Automatically crawl, scrape, chunk and embed web pages.
Nov 2025
Sparse Vector Search
First class support for BM25 and SPLADE vectors.
Oct 2025
Introducing Chroma Sync
Automatically chunk, embed, and index GitHub repos.
Oct 2025
wal3: Chroma's Write-Ahead Log
A Write-Ahead Log for Chroma, Built on Object Storage
Sep 2025
Package Search MCP
Query thousands of open-source repos through MCP.
Sep 2025
Collection Forking
Fast duplication of collections with copy-on-write.
Aug 2025
Introducing Chroma Cloud
Chroma Cloud is now generally available.
Aug 2025
Designing a query execution engine
A push-based, morsel-driven execution engine in Rust.
Aug 2025
70% Data Throughput Increase
Performance boost using base64 vector encoding.
Jul 2025
Regex Search Support
Search using regular expressions with new operators.
Jun 2025
JavaScript Client V3
Complete rewrite with reduced bundle size.
Jun 2025
We’re looking for curious people who are dedicated to becoming world-class at their craft to join our team.
See open roles
Get started
Get up and running in 30 seconds or less with $5 in free credits.
Quick Start
Python
Python
getting started docs →
pip install chromadb
JavaScript / TypeScript
JavaScript / TypeScript
getting started docs →
npm install chromadb
View full documentation →
Start free on Cloud
Read the docs
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2026
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