
Vespa
8.4#1 in ai search and discovery platforms softwareWebAPILinuxmacOS
Visit
| Fact | Vespa | Weaviate |
|---|---|---|
| Deployment | Vespa can be self-managed, run with the Vespa Kubernetes Operator, or deployed on Vespa Cloud. | Weaviate can run as a hosted service or a self-managed instance locally or with a cloud provider; deployment options include Docker and Kubernetes. |
| Founded | Gartner Peer Insights lists Vespa’s founding year as 2023. | 2019 |
| Free plan | No | Yes |
| Integrations | Vespa Cloud Enclave can run applications in customer accounts on AWS, Azure, or Google Cloud Platform. | The integration ecosystem lists cloud and model integrations including AWS, Google Cloud, Azure, OpenAI, Anthropic, Cohere, Hugging Face, and Ollama. |
| Product | Vespa is an AI search platform for online data-driven applications that combines retrieval, ranking, machine-learning inference, and real-time serving. | 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 | Vespa supports vector and tensor search, positional text search, and search over structured data. | The database supports hybrid search that combines vector and BM25 keyword search, along with semantic and keyword search. |
| Security | 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. | 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 Startup plan includes community support only with no SLA; Cloud plans list unlimited support cases, with response times varying by plan. | 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. |
Vespa suits teams building AI applications that depend on search quality, ranking, fresh real-time data, or increasing retrieval traffic. It offers local, self-managed, and cloud deployment options.
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.