Vector Databases

Vector databases store and query high-dimensional embeddings generated by machine learning models, enabling semantic search, recommendation systems, and retrieval-augmented generation. The category is young and evolving fast, with several European-founded providers. Key differentiators are indexing algorithm support (HNSW, IVF), query latency at scale, and integration with popular ML frameworks.

5 European providers