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This survey paper provides an overview of the landscape, technologies, and applications of vector databases, making it a valuable resource for understanding the field.
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.
A comprehensive research paper outlining the fundamental concepts, practical use-cases, and current challenges in the field of vector database management systems.