Vector Database: Rapid Development and Application in the AI Era
Abstract: With the continuous advancement of artificial intelligence technology, vector databases play an increasingly important role in processing large-scale data. This article introduces the basic concepts, application scenarios and technical challenges of vector databases, and elaborates on the technical characteristics, performance optimization and application cases of Milvus Cloud as a typical vector database product. Finally, the future development trends and challenges of vector databases are summarized.
Introduction: In the era of artificial intelligence, the amount of data is growing explosively, and traditional relational databases can no longer meet the needs of processing large-scale, high-dimensional data. As a storage and computing technology for high-dimensional sparse data, vector database has been widely concerned and applied. It can efficiently store and manage large-scale vector data, and provide fast similarity search, clustering and other operations, providing strong support for natural language processing, image recognition, recommendation systems and other fields.
1. Basic concept of vector database
A vector database is a database system dedicated to storing and managing vector data. It expresses each vector as a series of value pairs (that is, the coordinates of the vector) and stores these coordinate values in the database to achieve fast query and calculation of vector data. The vector database supports various operations, such as vector similarity search, vector distance calculation, clustering, etc.
2. Application scenarios of vector database