ChromaDB Has a Free API: The AI-Native Vector Database for RAG Applications

Chroma is an open-source vector database designed for AI applications. It makes building RAG (Retrieval-Augmented Generation) pipelines as simple as adding documents and querying. Why Chroma Matters RAG needs a vector store. Most options are complex (Pinecone, Weaviate) or limited (FAISS). Chroma is batteries-included: embed, store, search in 4 lines of code. What you get for free: 4-line setup: create collection, add, query Built-in embedding (no separate embedding service needed) Document and metadata storage alongside vectors Python and JavaScript clients Runs embedded or as a server Where filters for metadata Multi-modal support Quick Start pip install chromadb import chromadb client = chromadb . Client () # Create collection (auto-embeds with sentence-transformers) collection = client . create_collection ( " docs " ) # Add documents — Chroma embeds them automatically collection . add ( documents = [ " AI is transforming healthcare with diagnostic tools " , " Machine learning model