Milvus
6.3#13 in vector databasesFree planFree planAPILinuxSelf-hosted
Visit| Fact | Milvus | Weaviate |
|---|---|---|
| Deployment | Milvus offers Lite as a Python library, Standalone as a single-machine server, and Distributed for Kubernetes clusters. | Weaviate can run as a hosted service or a self-managed instance locally or with a cloud provider; deployment options include Docker and Kubernetes. |
| Free plan | Yes | Yes |
| Integrations | The integrations documentation lists tools including LangChain, LlamaIndex, Haystack, DSPy, Dify, Langflow, OpenAI, Cohere, and HuggingFace. | The integration ecosystem lists cloud and model integrations including AWS, Google Cloud, Azure, OpenAI, Anthropic, Cohere, Hugging Face, and Ollama. |
| Intended users | The documentation describes Distributed as suited to enterprise users running large-scale vector search systems in production. | The company describes Weaviate as infrastructure for developers and says its deployments serve startups, scale-ups, and enterprises. |
| Product | Milvus is an open-source vector database built for GenAI applications. | Weaviate is an open-source AI vector database for storing, indexing, and searching high-dimensional vectors, used as a foundation for search, RAG, and agents. |
| Search | Milvus supports approximate nearest neighbor, filtering, range, hybrid, and full-text search, plus reranking, fetch, and query operations. | The database supports hybrid search that combines vector and BM25 keyword search, along with semantic and keyword search. |
| Security | Milvus documents user authentication, TLS encryption for gRPC and REST traffic, and role-based access control. | The security page states that Weaviate Cloud encrypts data in transit and at rest, supports role-based access controls, and provides automated daily backups. |
| Support | The Milvus site lists community channels including Slack, Discord, GitHub, and Milvus Office Hours. | Free includes Basic Support; Flex lists Standard Support with next-business-day Sev 1 response, while Premium lists enterprise support as fast as 1-hour Sev 1. |
Milvus suits developers and teams building vector search into GenAI applications, from local experiments to large Kubernetes deployments. Its Lite option can also suit users who need local search over private or sensitive data.
Weaviate is aimed at developers building search, RAG, or agent infrastructure. Its deployment options may suit teams ranging from startups to enterprises that want hosted or self-managed operation.