What is a Vector Database?

Introduction The use of vector databases has revolutionized data administration. They primarily address the requirements of contemporary applications handling high-dimensional data. Traditional databases use tables and rows to store and query structured data.

Vector databases manage data using high-dimensional vectors or numerical arrays representing intricate characteristics of diverse data types like text, photos, or user activity. Vector databases have become an increasingly helpful tool as data-driven applications must comprehend and interpret the complex interactions between data points. Overview Learn about vector databases, how they work, and their features.

Gain an understanding of its application in various domains. Discover popular vector database solutions and comparison with traditional databases. Table of contents What is a Vector Database? Vector databases are specialized databases that effectively store, manage, and query high-dimensional vector representations of data.

Vector databases concentrate on data in vectors, numerical arrays representing various forms of information, including text, graphics, or user activity, as opposed to standard databases that manage structured data using tables and rows. These vectors distill the core of the data in a way that is useful for machine learning applications and similarity searches. Vector databases allow you to retrieve data based on its semantic content instead of a precise match between text and numbers, cluster co.