In contrast, AWS is proposing that enterprises use a new type of S3 bucket purpose-built for storing and querying vector data via a dedicated set of APIs, Amazon S3 Vector, that it says eliminates the need for provisioning infrastructure for a vector database.
Raya Mukherjee, senior analyst at Everest Group, said Amazon S3 or any other cloud-based object storage is cheaper to run and maintain compared to vector databases due to differences in their structure and hardware requirements and thus will help enterprises simplify architecture, reduce operational overhead and decrease cost, said.
While object storage is designed to handle vast volumes of unstructured data using a flat architecture that minimizes overhead and supports efficient retrieval of individual files, vector databases are engineered for high-performance similarity search across complex, high-dimensional data and often rely on specialized indexing methods and hardware acceleration that can drive up infrastructure and operational expenses.
