Milvus

Scalable Vector Database

An open-source vector database built for trillion-scale similarity search with hybrid queries, 72% memory compression via RaBitQ, and natural language management through MCP.

MilvusVector Database📊Trillion Sc...🔍Hybrid Sear...📦RaBitQ🏢Multi-Tenan...🔌MCP Support📖Open Source

Click on any feature node to explore Milvus's capabilities

Core Capabilities

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Trillion-Scale Search

  • Trillion vector capacity
  • Distributed architecture
  • Horizontal sharding
  • Load balancing
  • High availability
🔍

Hybrid Search

  • Dense vector similarity
  • Sparse/BM25 search
  • Combined ranking
  • Metadata filtering
  • Range queries
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Index Types

  • HNSW for accuracy
  • IVF for scale
  • RaBitQ quantization
  • GPU-accelerated indices
  • Auto-index selection
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Multi-Tenancy

  • Partition-based isolation
  • RBAC access control
  • Resource quotas
  • Tenant-level metrics
  • Data encryption
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MCP Integration

  • Natural language queries
  • Conversational management
  • Schema operations via chat
  • AI-assisted administration
  • LLM tool integration
🚀

Deployment

  • Kubernetes operator
  • Docker Compose
  • Zilliz Cloud managed
  • On-premises clusters
  • Hybrid deployments

Why We Deploy Milvus

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Unmatched Scale

When you need trillion-scale vector search, Milvus delivers. Distributed architecture handles workloads other databases can't touch.

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RaBitQ Compression

72% memory reduction with minimal accuracy loss. Run massive indices on reasonable hardware without sacrificing search quality.

🔍

True Hybrid Search

Combine dense vectors with sparse BM25 and metadata filtering in single queries. The complete search solution.

🔌

MCP Natural Language

Manage your database with conversational AI. Query, configure, and administer through natural language commands.

Production Proven

Used by thousands of organizations worldwide. Battle-tested at scale with comprehensive tooling and support.

🚀

Flexible Deployment

Self-host on Kubernetes, run via Docker, or use Zilliz Cloud. Deploy where and how your organization needs.

Common Use Cases

Organizations deploy Milvus when they need vector search at scale with enterprise-grade reliability.

Large-Scale RAG
Enterprise knowledge bases with millions of documents
E-commerce Search
Product similarity across massive catalogs
Image & Video Search
Visual similarity at billion-image scale
Recommendation Engine
Real-time personalization for millions of users
Fraud Detection
Anomaly detection in high-dimensional data
Drug Discovery
Molecular similarity search at scale
Multi-Tenant SaaS
Vector search with tenant isolation
Genomic Analysis
DNA/RNA sequence similarity matching

Ready for Trillion-Scale Search?

We can help you deploy and scale Milvus for your large-scale vector search and AI applications.