Aurora PG Vector

Aurora PG Vector is an extension of Amazon Aurora PostgreSQL, designed to efficiently handle and store high-dimensional vector data. This capability is particularly useful for machine learning and AI applications, such as natural language processing (NLP) and image recognition, where embeddings or feature vectors are generated to represent complex data. Aurora PG Vector allows for fast, scalable, and optimized similarity searches using these vectors, enabling operations like nearest neighbor search. It's integrated into Amazon Aurora's managed database environment, offering seamless support for vector-based queries alongside traditional relational data.