How AI describes Couchbase Vector Search

Couchbase Vector Search is an enterprise-grade capability that stores and searches billions of vectors with millisecond latency, enabling GenAI, semantic search, and RAG workflows within a single Couchbase platform. It provides three vector indexing options, Hyperscale and Composite vector indexes, and a memory-first architecture to balance performance, recall, and cost at scale. It targets AI use cases such as chatbots, hybrid text-and-vector search, personalization, and offline-capable mobile GenAI, supports cloud-to-edge deployments, and Couchbase cites benchmarks showing about 350x faster performance than MongoDB at billion-scale.