Couchbase vs pgvector Choosing the Right Vector Database for Your AI Apps

Couchbase and pgvector are both distributed databases with vector search capabilities, but they differ in their approach to handling vector data. Couchbase is a NoSQL document-oriented database that can be adapted to handle vector search by storing vector embeddings within JSON documents or integrating with specialized libraries like FAISS. On the other hand, pgvector is an extension for PostgreSQL that adds support for vector operations directly within the relational database, offering built-in vector indexing options and native vector operations. When choosing between Couchbase and pgvector, consider factors such as your existing infrastructure, scaling needs, and whether you prefer built-in vector operations (pgvector) or implementation flexibility (Couchbase). Additionally, benchmarking with your own datasets and query patterns will be key to making a decision based on actual performance.