About Vespa
An open-source platform for large-scale search and AI applications that combines vector search, text search, and distributed ML inference to build real-time, relevance-driven applications.
Key Features
- Native support for vectors, tensors, text, and structured data with integrated machine-learned ranking and real-time inference.
- Designed for production at scale (billions of items, thousands QPS) and advanced hybrid retrieval/re-ranking workflows.
- Developer-focused tools, sample apps, and a managed offering for enterprise deployments.
Use Cases & Best For
Teams building advanced search, RAG, and recommendation systems that need integrated ranking/inference and low-latency retrieval at scale.
Organizations requiring fine-grained relevance control combining vectors and structured signals in production.
About Vector Databases
Storage and retrieval for embeddings