Milvus vs Vespa
Milvus
milvus.ioVespa
vespa.aiSide by side
| Figure | Milvus | Vespa |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | Yes |
| Open source | — | Yes |
| Web | — | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 7 |
| Spec score · Ai Databases | 8.3 (#8) | 8.7 (#5) |
| Spec score · Vector Databases | 8.2 (#7) | 8.8 (#3) |
| Spec score · AI Search and Discovery Platforms Software | 8.1 (#9) | 8.7 (#3) |
| Spec score · Search Databases | 8.2 (#11) | 8.7 (#5) |
| Spec score · Database Software | 8.2 (#39) | 8.8 (#17) |
| Deployment | Milvus offers Lite as a Python library, Standalone as a single-machine server, and Distributed for Kubernetes clusters. | Vespa can be self-managed, run with the Vespa Kubernetes Operator, or deployed on Vespa Cloud. |
| Free plan | Yes | No |
| Integrations | The integrations documentation lists tools including LangChain, LlamaIndex, Haystack, DSPy, Dify, Langflow, OpenAI, Cohere, and HuggingFace. | Vespa Cloud Enclave can run applications in customer accounts on AWS, Azure, or Google Cloud Platform. |
| Product | Milvus is an open-source vector database built for GenAI applications. | Vespa is an AI search platform for online data-driven applications that combines retrieval, ranking, machine-learning inference, and real-time serving. |
| Search | Milvus supports approximate nearest neighbor, filtering, range, hybrid, and full-text search, plus reranking, fetch, and query operations. | Vespa supports vector and tensor search, positional text search, and search over structured data. |
| Security | Milvus documents user authentication, TLS encryption for gRPC and REST traffic, and role-based access control. | The Vespa Cloud security guide describes data-plane requests protected with mutual TLS or, optionally, tokens, and says Vespa.ai has a SOC 2 attestation. |
| Support | The Milvus site lists community channels including Slack, Discord, GitHub, and Milvus Office Hours. | The Startup plan includes community support only with no SLA; Cloud plans list unlimited support cases, with response times varying by plan. |
| What it does | Milvus is an open-source vector database developed by Zilliz for high-performance, scalable vector search. | Vespa is a data platform for storing, searching, and processing large structured and unstructured datasets with real-time indexing, filtering, recommendations, and personalization. |
Plans
Vespa
- StartupPrice not published
- BasicPrice not published
- CommercialPrice not published
- EnterprisePrice not published
- StartupFree
- Enterprise *$0.18 a month
- Self ManagedPriced on request
In their own words
Milvus
Milvus is an open-source vector database from Zilliz for GenAI and scalable vector search. It supports approximate-nearest-neighbor, filtered, range, hybrid, and full-text search, along with reranking, fetch, and query operations. Metadata filtering, sparse vectors, and index types including HNSW, IVF, FLAT, DiskANN, and SCANN are documented. Deployment choices are Milvus Lite as a Python library, Standalone as a single-machine server, and Distributed on Kubernetes. Documentation recommends Lite for up to a few million vectors, Standalone up to 100 million, and Distributed for 100 million to tens of billions. Lite can run locally without a cloud service for private or sensitive data; an online upgrade from Standalone to a cluster is not currently supported. Official interfaces include REST plus Python, Go, Java, Node.js, and C++ APIs or SDKs. C# is contributed by Microsoft and Rust is under development. Security documentation covers authentication, TLS for gRPC and REST, and role-based access control at collection, database, and instance levels. The Apache 2.0 software is free, and Zilliz Cloud is offered as a managed option.
Vespa
Vespa is an AI search platform for online applications that use data, retrieval, ranking, machine-learning inference, and real-time serving. It supports vector and tensor search, positional text search, and queries over structured data. Ranking signals can be combined with tensor functions or machine-learned models, including ONNX and XGBoost formats; model inference can use ONNX Runtime. Vespa distributes functions across node clusters and allows cluster size changes without affecting queries or writes. Teams can self-manage deployments, use the Vespa Kubernetes Operator, or run on Vespa Cloud. Local deployment guidance lists Linux, macOS, and Windows 10 Pro on x86_64 or arm64 with Docker Desktop or Podman Desktop. Vespa Cloud includes encryption at rest and in transit, certificates for nodes and endpoints, and automatic operating system patching. Its trial provides $300 in credits without requiring a credit card, then stops the application when credits are used. Cloud plans have quotas, and Startup is limited to development zones. Pricing is listed from $0.05 a month, with metered resource rates.