Milvus

Milvus

Milvus is a purpose-built open-source vector database designed for high-performance similarity search at scale. It supports multiple index types (HNSW, IVF, FLAT, SCANN) and hybrid scalar+vector filtering, making it the vector layer for production RAG, recommendation, and multimodal search applications.

Key Features

• Billion-scale search: Horizontally scalable with independent compute and storage nodes
• Multiple index types: HNSW, DiskANN, IVF_FLAT, IVF_SQ8, SCANN for different speed/accuracy trade-offs
• Hybrid search: Combine dense vector ANN with sparse BM25 keyword and scalar field filters
• Multi-tenancy: Collection-level isolation with role-based access control
• Streaming ingestion: Real-time data ingestion via Kafka/Pulsar integration
• MilvusLite: Embedded mode that runs in-process for development and edge deployments

Quick Start

# Start Milvus standalone
wget https://raw.githubusercontent.com/milvus-io/milvus/master/scripts/standalone_embed.sh
bash standalone_embed.sh start

pip install pymilvus

from pymilvus import MilvusClient

client = MilvusClient("milvus_demo.db")  # MilvusLite
client.create_collection("my_embeddings", dimension=768)
client.insert("my_embeddings", [{"id": 1, "vector": [0.1]*768}])
results = client.search("my_embeddings", data=[[0.1]*768], limit=5)

Add to ai-supply

npx ai-supply add milvus-vector-database

Curated mirror of the open-source Milvus (Apache-2.0). Get it from the source.