Milvus Has a Free Vector Database Built for Billion-Scale AI Similarity Search

Milvus is an open-source vector database designed for billion-scale vector similarity search. It powers AI applications at NVIDIA, Samsung, and Walmart.

What You Get for Free

• Billion-scale — handles 10B+ vectors
• Multiple indexes — IVF, HNSW, DiskANN, GPU indexes
• Hybrid search — vector + scalar filtering
• Schema-based — define collections with typed fields
• Partitions — organize data for efficient queries
• Time Travel — query historical data snapshots
• Multi-language SDKs — Python, Java, Go, Node.js

Quick Start

docker compose up -d  # Milvus standalone
pip install pymilvus

Insert and Search (Python)

from pymilvus import MilvusClient

client = MilvusClient('http://localhost:19530')

client.create_collection('articles', dimension=384)

client.insert('articles', [
    {'id': 1, 'vector': [0.1]*384, 'title': 'AI trends'},
    {'id': 2, 'vector': [0.2]*384, 'title': 'ML basics'},
])

results = client.search('articles', data=[[0.1]*384], limit=5)

Milvus vs Qdrant

Feature	Milvus	Qdrant
Scale	Billion+	Millions
GPU index	Yes	No
Language	Go/C++	Rust
Complexity	Higher	Lower

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Need vector database setup? Check my work on GitHub or email [e-mail] for consulting.