Chroma: Open Source Embedding Database

Overview Chroma (ChromaDB) is a rapidly growing open-source vector database designed for "Developer Experience" (DX). It focuses on being the easiest way to add state to your AI application.

Key Features

1. Embedded Mode Chroma runs in-process (inside your Python script) just like SQLite.

• No Docker container to spin up.
• no external server to manage.
• pip install chromadb and go.

2. Client/Server Mode When you scale, you can switch it to run as a standalone server so multiple apps can connect to it.

3. Batteries Included Chroma has built-in embedding functions. You don't need to generate vectors manually.

import chromadb
client = chromadb.Client()
collection = client.create_collection("my_docs")

# Chroma automatically tokenizes & embeds this text using SentenceTransformers by default
collection.add(
    documents=["This is a document", "This is another"],
    ids=["id1", "id2"]
)

results = collection.query(
    query_texts=["This is a query context"],
    n_results=2
)

Use Case Chroma is the default choice for:

• Python notebooks.
• Prototypes / MVPs.
• Local LLM apps (PrivateGPT).
• Apps where simplicity is the priority.