ChromaDB is an open-source embedding database that makes it easy to build AI applications with memory. Store, search, and retrieve embeddings with just a few lines of Python.
Why ChromaDB is the Easiest Way to Add AI Memory
A developer building a chatbot needed semantic search over 50,000 documents. Setting up Elasticsearch with embeddings took a week. ChromaDB did it in 10 lines of Python.
Key Features:
- Simple API — 4 functions: add, query, update, delete
- Automatic Embeddings — Built-in embedding functions
- Metadata Filtering — Filter results by any metadata field
- Persistent Storage — SQLite-backed for easy deployment
- Multi-Modal — Text, images, and custom embeddings
Quick Start
pip install chromadb
import chromadb
client = chromadb.Client()
collection = client.create_collection("docs")
collection.add(
documents=["Python is great", "JavaScript is versatile", "Rust is fast"],
ids=["1", "2", "3"]
)
results = collection.query(query_texts=["fast programming language"], n_results=2)
print(results["documents"]) # [["Rust is fast", "Python is great"]]
With Metadata
collection.add(
documents=["Deploy with Docker"],
metadatas=[{"category": "devops", "difficulty": "beginner"}],
ids=["4"]
)
results = collection.query(
query_texts=["deployment"],
where={"category": "devops"}
)
Why Choose ChromaDB
- Simplest API — 4 functions to learn
- Auto embeddings — no embedding pipeline needed
- Zero infrastructure — runs in-process or as server
Check out ChromaDB docs to get started.
Building AI apps? Check out my Apify actors or email spinov001@gmail.com for data extraction.
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