Brendan Tierney gives us an overview of vector databases:
A Vector Database is a specialized database designed to efficiently store, search, and retrieve high-dimensional vectors, which are often used to represent complex data like images, text, or audio. Vector Databases handle the growing need for managing unstructured and semi-structured data generated by AI models, particularly in applications such as recommendation systems, similarity search, and natural language processing. By enabling fast and scalable operations on vector embeddings, vector databases play a crucial role in unlocking the power of modern AI and machine learning applications.
It’s interesting to see this pop up as a standalone database type (e.g., chromadb), though we’re also seeing some existing players like Postgres support vector database functionality via extension.