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Vector database management systems, often simply called vector databases, are systems optimized for efficient storage, indexing, and querying of high-dimensional vector data. They use specialized algorithms and data structures to support similarity search, often used in machine learning or data mining, with a focus on performance, scalability and flexibility. Vector DBMSs can typically handle multiple data types, including numerical, text and binary. They can store metadata associated with each vector, and they can efficiently store sparse vectors.
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