Couchbase and Pinecone are both distributed databases designed to store and query high-dimensional vectors, which are numerical representations of unstructured data. They play a crucial role in AI applications by enabling efficient similarity searches for tasks like recommendation systems or retrieval-augmented generation. While Couchbase is an open-source NoSQL database that can be adapted for vector search, Pinecone is a purpose-built vector database with native support for vector indexes and compatibility with machine learning models. The choice between the two depends on factors such as infrastructure preferences, scaling needs, and whether vector search is primary or secondary in your application architecture.