Using Vector Databases for High-Dimensional Data

This limitation has paved the way for specialised vector databases to address the unique challenges posed by high-dimensional data. Vector representation: At the core of vector databases lies the concept of vector representation. Indexing techniques: Vector databases leverage various indexing techniques to organise and structure the vector data efficiently. As the volume of high-dimensional data increases, vector databases can adapt and accommodate the expanding storage and computational requirements without sacrificing performance. Centralised training data: Vector databases serve as a centralised repository for training data in machine learning applications.