AWS vector solutions: Build agentic AI where your data lives
Amazon Web Services Marc Trimuschat
AWS is positioning “AWS vector solutions” as a way to add retrieval for agentic AI without moving or duplicating data across systems. The announcement highlights that Amazon OpenSearch Serverless autoscales 20x faster than its previous generation and can provision in seconds. As a result, teams can choose among different AWS vector engines (including OpenSearch, S3 Vectors, and DynamoDB vector search) to match latency, cost, and access patterns for RAG and semantic retrieval workloads.
Why it matters
AWS offers a broad portfolio of vector search built directly into the databases and storage services you already use, with no standalone vector database or data migration required. This post covers six purpose-built services, a decision framework for choosing the right engine, and customer proof points for each.