Selecting a vector store for Amazon Bedrock Knowledge Bases
Amazon Web Services 4 weeks ago 36
Amazon Bedrock Knowledge Bases guidance compared three customer-managed vector store backends for RAG—Amazon OpenSearch Service, Amazon Aurora PostgreSQL with pgvector, and Amazon S3 Vectors—showing how vector-store choice affects retrieval performance and cost across different use cases. Amazon S3 Vectors can reduce vector storage costs by up to 90 percent compared with traditional vector databases (and the post also notes OpenSearch Serverless NextGen collections planned for May 2026 are not yet compatible with the Bedrock Knowledge Bases Retrieve API). The benchmarks and tuning recommendations change how teams should select embeddings, indexing, and storage options so they can trade off latency, cost, and retrieval quality for their workloads.