What Are Vector Databases in AI and How AWS Services Help in Implementation?

Artificial Intelligence (AI) applications, particularly those involving large language models (LLMs), computer vision, and recommendation systems, rely on efficient ways to store, search, and retrieve high-dimensional data. This is where vector databases come into play. These specialized databases are designed to handle embeddings—numerical representations of data points—allowing for fast similarity searches.

Amazon Web Services (AWS) offers several solutions for implementing and managing vector databases at scale, ensuring high availability, security, and performance. In this article, we’ll explore what vector databases are, why they matter in AI applications, and which AWS services can help build and deploy them effectively.

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