A storage system designed to efficiently store and retrieve vector representations of data objects. Vector databases are optimized for handling high-dimensional vectors, which are commonly used in machine learning and natural language processing tasks such as similarity search, recommendation systems, and semantic indexing. These databases typically provide fast query performance and support operations such as nearest neighbor search, vector indexing, and similarity computation. Vector databases play a crucial role in enabling scalable and efficient processing of large-scale vector data in applications where similarity or distance metrics are essential for data retrieval and analysis.
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