Vector databases, often referred to as "vectordbs," are specialized database systems designed to store, manage, and query vector embeddings efficiently. These databases are tailored to handle high-dimensional numerical representations of data that capture semantic relationships, making them particularly suitable for tasks like similarity search, recommendation systems, natural language processing, and machine learning applications.
