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Chroma
The simplest open-source vector database — get started in 3 lines of Python.
0Open Source
Vector Database
Overview
Chroma is the open-source AI-native embedding database, designed to be simple to use for prototyping and production RAG applications with minimal setup.
Key Features
- In-memory mode for instant prototyping
- Persistent storage mode for production use
- Client-server mode with REST API
- Built-in embedding functions for OpenAI, Cohere, HuggingFace
- Metadata filtering and full-text search
- Simple Python and JavaScript SDKs
Real-World Workflows
Prototype a RAG app in minutes
- 1pip install chromadb and create an in-memory client
- 2Add documents — Chroma auto-embeds them
- 3Query with natural language and get relevant chunks
- 4Plug results into your LLM prompt for grounded answers
Getting Started
pip install chromadb
import chromadb
client = chromadb.Client()
collection = client.create_collection('docs')
collection.add(documents=['AI is transforming software'], ids=['1'])
results = collection.query(query_texts=['What is AI doing?'], n_results=1)
print(results)Compare Alternatives
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