ChromaDB

Overview

ChromaDB is an open-source embedding database designed for simplicity and developer experience. It is the easiest vector database to get started with, running embedded in your application without requiring a separate server process.

ChromaDB can automatically generate embeddings from your documents using built-in embedding functions (OpenAI, Cohere, HuggingFace, etc.), or you can provide pre-computed embeddings. Its API is minimal and intuitive: add documents, query by similarity, filter by metadata.

The database supports both in-memory and persistent storage modes, making it ideal for development, testing, and small-to-medium production workloads. For larger scale applications, it can run as a client-server architecture.

When to Use

Choose ChromaDB for prototyping RAG applications, small-to-medium scale projects, and development environments where you want the simplest possible vector database setup. For large-scale production, consider Qdrant, Pinecone, or Weaviate.

Getting Started

pip install chromadb

import chromadb

client = chromadb.Client()
collection = client.create_collection("my_docs")
collection.add(documents=["Hello world"], ids=["1"])
results = collection.query(query_texts=["greeting"], n_results=1)