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Amazon S3

Amazon S3 Control

AWS S3 Control provides access to Amazon S3 control plane actions.

Amazon S3 Files

S3 Files makes S3 buckets accessible as high-performance file systems powered by EFS. This service enables file system interface access to S3 data with sub-millisecond latencies through mount targets, supporting AI/ML workloads, media processing, and hybrid storage workflows that require both file system and object storage access to the same data.

Amazon S3 on Outposts

Amazon S3 on Outposts provides access to S3 on Outposts operations.

Amazon S3 Tables

An Amazon S3 table represents a structured dataset consisting of tabular data in Apache Parquet format and related metadata. This data is stored inside an S3 table as a subresource. All tables in a table bucket are stored in the Apache Iceberg table format. Through integration with the AWS Glue Data Catalog you can interact with your tables using AWS analytics services, such as Amazon Athena and Amazon Redshift. Amazon S3 manages maintenance of your tables through automatic file compaction and snapshot management. For more information, see Amazon S3 table buckets.

Amazon S3 Vectors

Amazon S3 vector buckets are a bucket type to store and search vectors with sub-second search times. They are designed to provide dedicated API operations for you to interact with vectors to do similarity search. Within a vector bucket, you use a vector index to organize and logically group your vector data. When you make a write or read request, you direct it to a single vector index. You store your vector data as vectors. A vector contains a key (a name that you assign), a multi-dimensional vector, and, optionally, metadata that describes a vector. The key uniquely identifies the vector in a vector index.