This is a demo directory website built with Ever Works
A comprehensive academic survey that explores the architecture, storage, retrieval techniques, and challenges associated with vector databases. It categorizes algorithmic approaches to approximate nearest neighbor search (ANNS) and discusses how vector databases can be integrated with large language models, offering valuable insights and foundational knowledge for understanding and building vector database systems.
An overview of the architectural components common to Vector Database Management Systems (VDBMS), which are designed to efficiently store, index, and query high-dimensional vector embeddings. This provides foundational knowledge for anyone interested in the internal workings of vector databases.
Page 1 of 1