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Tool Comparison
Weaviate
Open-source vector database with built-in embedding and hybrid search.
VS
At a Glance
| Attribute | Weaviate | Milvus |
|---|---|---|
| License / Pricing | Open Source | Open Source |
| Type | ai | ai |
| GitHub Stars | — | — |
| Rating | 4.5/5 | 4.3/5 |
| Key Features | 6 listed | 6 listed |
| Integrations | 5 listed | 4 listed |
| Categories | Vector Database | Vector Database |
Key Features
Weaviate
- Built-in vectorization modules (OpenAI, Cohere, HuggingFace)
- Hybrid search combining BM25 keyword and vector search
- GraphQL and REST APIs
- Multi-tenancy for SaaS applications
- Generative search — query + LLM response in one call
- Cloud-managed or self-hosted with Docker/Kubernetes
Milvus
- Billion-scale vector search with distributed architecture
- Multiple index types: HNSW, IVF, DiskANN
- Milvus Lite — embedded mode for local development
- Time Travel — query data at any historical timestamp
- Dynamic schema for schema-on-write flexibility
- Zilliz Cloud managed offering
Real-World Use Cases
Weaviate
Build generative search over your knowledge base
Start Weaviate with docker-compose (includes vectorizer module)
Milvus
Production-scale image similarity search
Extract image embeddings using a vision model (CLIP, ResNet)
Integrations
Weaviate
langchainllamaindexopenaihuggingfacedspy
Milvus
langchainllamaindexopenaihuggingface
🏆 Which should you choose?
Choose Weaviate if…
- → you're already in the Vector Database ecosystem and prefer Weaviate's workflow
Choose Milvus if…
- → you're already in the Vector Database ecosystem and prefer Milvus's workflow