Amazon S3 Vectors, announced at the AWS Summit in New York, is the first cloud object store with native support for large vector datasets. It offers subsecond query performance and lowers the cost of storing AI-ready data compared to traditional vector databases. S3 Vectors includes vector buckets, where developers can create and manage vector indexes for similarity searches. Each vector bucket can hold up to 10,000 indexes, enabling extensive organization of vector data. Additionally, it integrates with services like Bedrock Knowledge Bases and OpenSearch to enhance workload efficiency.
With S3 Vectors, you can now economically store the vector embeddings that represent massive amounts of unstructured data such as images, videos, documents, and audio files, enabling scalable generative AI applications including semantic and similarity search, RAG, and build agent memory.
Through its integration with Amazon OpenSearch Service, you can lower storage costs by keeping infrequent queried vectors in S3 Vectors and then quickly move them to OpenSearch as demands increase or to support real-time, low-latency search operations.
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