What is a Vector Database?
A Vector Database, at its essence, is a relational database system specifically designed to process vectorized data. Unlike conventional databases that contain information in tables, rows, and columns, vector databases work with vectors–arrays of numerical values that signify points in multidimensional space.
Vectors, in turn, are everywhere and are commonly used in, for instance, machine learning, artificial intelligence, genomics, and geospatial analysis. At these datasets, there are frequently high-dimensional vectors where each dimension represents a particular attribute or feature.
Such data place a heavy burden on traditional databases as they are tabular in form and do not allow efficiency in the storage and retrieval of such data and there comes the bottleneck in the performance of the database.
What is a Vector Database?
In the field of data handling, the standard database has been an icon for storing and retrieving data. Nevertheless, despite the fact that the amount of data and complexity are constantly increasing, there are new technologies appearing that break the previous limitations of conventional database systems.
Of the many innovations that have come with the Vector Database is a strong tool that can manage high dimensional data in a more efficient manner. This article looks at what a Vector Database is, how it functions, and the potential it holds for the evolution of data storage.
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