ConfigsMar 31, 2026·2 min read

Chroma — Open-Source Vector Database for AI

Chroma is the open-source vector database and data infrastructure for AI applications. 27.1K+ GitHub stars. Simple 4-function API for embedding, storing, and querying documents. Supports Python, JavaS

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Quick Use

Use it first, then decide how deep to go

This block should tell both the user and the agent what to copy, install, and apply first.

# Install Python client
pip install chromadb

# Or JavaScript
npm install chromadb

# Quick start
python -c "
import chromadb
client = chromadb.Client()
collection = client.create_collection('docs')
collection.add(documents=['AI is amazing', 'Vector search is fast'], ids=['1', '2'])
results = collection.query(query_texts=['artificial intelligence'], n_results=1)
print(results)
"
Intro

Chroma is the open-source data infrastructure for AI — a vector database designed to make it easy to build AI applications with embeddings. With 27,100+ GitHub stars and Apache 2.0 license, Chroma provides a simple 4-function API: create a collection, add documents, query by similarity, and retrieve by ID. It handles tokenization, embedding, and indexing automatically. Chroma supports Python, JavaScript/TypeScript, Go, and Rust clients, and offers both local and cloud deployment options.

Best for: Developers building RAG pipelines, semantic search, or any AI app that needs vector similarity search Works with: Claude Code, OpenAI Codex, Cursor, Gemini CLI, Windsurf Clients: Python, JavaScript/TypeScript, Go, Rust

Key Features

  • Simple 4-function API: create_collection, add, query, get — no complex setup
  • Automatic embedding: Built-in tokenization and embedding, or bring your own
  • Metadata filtering: Filter queries by document metadata and content
  • Multi-language clients: Python, JavaScript/TypeScript, Go, Rust
  • Local or cloud: Run embedded in your app or deploy as a server
  • Chroma Cloud: Serverless vector, hybrid, and full-text search

FAQ

Q: What is Chroma? A: Chroma is an open-source vector database with 27.1K+ stars for building AI applications. It provides automatic embedding, similarity search, and metadata filtering through a simple 4-function API. Apache 2.0 licensed.

Q: How do I install Chroma? A: Run pip install chromadb for Python or npm install chromadb for JavaScript. No external dependencies required for local use.

Q: How does Chroma compare to Pinecone or Weaviate? A: Chroma is fully open-source (Apache 2.0) and can run embedded in your application with zero infrastructure. Pinecone is cloud-only and proprietary. Weaviate is also open-source but heavier to deploy.

🙏

Source & Thanks

Created by Chroma. Licensed under Apache 2.0. chroma-core/chroma — 27,100+ GitHub stars

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