Weaviate vs Qdrant
Both are open source, but with different philosophies. Weaviate offers built-in ML modules (vectorize text, images automatically) and GraphQL API. Qdrant focuses on pure vector search speed (Rust) with a simple REST/gRPC API. Weaviate for ML-rich features; Qdrant for lean, fast search.
Weaviate
AI-native vector database with built-in vectorizers
GoBSD-3-Clauseopen-source
Key Features
- Built-in vectorization modules
- Hybrid BM25 + vector search
- GraphQL & REST APIs
- Multi-modal support
- Horizontal scaling
- RBAC & multi-tenancy
Pricing
Open SourceFree
Cloud (Sandbox)Free
Cloud (Standard)From ~$25/mo
EnterpriseCustom
Use Cases
Semantic searchGenerative search (RAG)ClassificationImage search
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
Weaviate if you need built-in vectorization. Qdrant if you want maximum speed with minimal overhead.
Choose Weaviate if you need:
- ✓Complete control over deployment and data
- ✓Source code access for customization
- ✓Built-in vectorization modules
- ✓Hybrid BM25 + vector search
- ✓GraphQL & REST APIs
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