Milvus vs Qdrant
Milvus is designed for massive scale (billions of vectors) with GPU acceleration and distributed architecture. Qdrant is leaner, faster for smaller-to-medium workloads, and simpler to deploy. Milvus for enterprise scale; Qdrant for developer-friendly simplicity.
Milvus
Distributed vector database built for scale
Go / C++Apache-2.0hybrid
Key Features
- Billion-scale vector search
- Separated compute & storage
- Multiple index types
- Strong consistency
- GPU acceleration
- Multi-language SDKs
Pricing
Open SourceFree
Zilliz Cloud (Free)$0
Zilliz CloudPay-as-you-go
Use Cases
Large-scale similarity searchRecommendation systemsDrug discoveryImage deduplication
Qdrant
High-performance vector search engine in Rust
RustApache-2.0open-source
Key Features
- Written in Rust for speed
- Rich payload filtering
- Multiple distance metrics
- Quantization support
- Distributed deployment
- gRPC & REST APIs
Pricing
Open SourceFree
Cloud (Free)$0
Cloud (Standard)From ~$15/mo
EnterpriseCustom
Use Cases
Similarity searchNeural searchMatching enginesRAG applications
Verdict
Milvus for billion-scale enterprise workloads. Qdrant for fast, simple deployments.
Choose Milvus if you need:
- ✓Billion-scale vector search
- ✓Separated compute & storage
- ✓Multiple index types
Choose Qdrant if you need:
- ✓Self-hosted deployment flexibility
- ✓No vendor lock-in or usage limits
- ✓Written in Rust for speed
- ✓Rich payload filtering
- ✓Multiple distance metrics