Vector Database

A vector database is designed to efficiently store and retrieve high-dimensional vectors, typically generated through embedding processes in machine learning. These databases are optimized for similarity searches, enabling rapid querying necessary in recommendation systems, image recognition tasks, and NLP applications. They handle operations like nearest neighbor search much faster than conventional databases, which makes them indispensable for handling large-scale high-dimensional data critical for modern AI workloads.