An S3 table represents a structured dataset consisting of underlying table data and related
metadata. This data is stored inside a table bucket as a subresource. All tables in a table bucket are
stored in the Apache Iceberg
To make tables in your account accessible by AWS analytics services, you integrate your Amazon S3 table buckets with Amazon SageMaker Lakehouse. This integration allows AWS analytics services such as Amazon Athena and Amazon Redshift to automatically discover and access your table data.
When you create a table, Amazon S3 automatically generates a warehouse location for the table. This is a unique S3 location that stores objects associated with the table. The following example shows the format of a warehouse location:
s3://63a8e430-6e0b-46f5-k833abtwr6s8tmtsycedn8s4yc3xhuse1b--table-s3Within your table bucket, you can organize tables into logical groupings called namespaces. For more information, see Table namespaces.
You can rename tables, but each table has its own unique Amazon Resource Name (ARN) and unique table ID. Each table also has a resource policy attached to it. You can use this policy to manage access to the table.
Table ARNs use the following format:
arn:aws:s3tables:region:owner-account-id:bucket/bucket-name/table/table-id
By default, you can create up to 10,000 tables in a table bucket. To request a quota
increase for table buckets or tables, contact Support
Amazon S3 supports the following types of tables in table buckets:
- Customer (self-managed) tables
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Customer tables are tables that you can read and write to. You can retrieve data from these tables using integrated query engines. You can insert, update, or delete data within them by using S3 API operations or integrated query engines.
- S3 managed tables
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AWS tables are read-only tables that are generated by an AWS service on your behalf. These tables are managed by Amazon S3 and can't be modified by any IAM principal outside of Amazon S3 itself. You can retrieve information from these tables, but you can't modify the data in them. AWS tables include S3 Metadata tables, which contain metadata that's captured from the objects within an S3 general purpose bucket. For more information, see Accelerating data discovery with S3 Metadata.
