Get started with Amazon S3 Tables
Amazon S3 Tables deliver the first cloud object store with built-in Apache Iceberg support and streamline storing tabular data at scale. Continual table optimization automatically scans and rewrites table data in the background for optimal query performance, which will continue to improve over time. S3 Tables include optimizations specific to Iceberg workloads that deliver up to 10x higher transactions per second compared to Iceberg tables stored in general purpose S3 buckets. Additionally, with the Intelligent-Tiering storage class, S3 Tables automatically optimize costs based on access patterns, without performance impact or operational overhead.
With S3 Tables support for the Apache Iceberg standard, your tabular data can be easily queried with popular Amazon Web Services and third-party query engines. Use S3 Tables to store tabular data such as daily purchase transactions, streaming sensor data, or ad impressions as an Iceberg table in S3, and optimize performance and cost as your data evolves using automatic table maintenance.
Benefits
Amazon S3 Tables Benefits
Scalability
Grow your data lake effortlessly–from your first table to enterprise scale–managing thousands of Iceberg tables without worrying about infrastructure or maintenance overhead.
Enhanced performance
Get faster query performance through continual table optimization–including advanced sort and z-order compaction–compared to unmanaged Iceberg tables, and up to 10x higher transactions per second compared to Iceberg tables stored in general purpose S3 buckets.
Fully managed
Automate table maintenance tasks including compaction, snapshot management, and unreferenced file removal to continually optimize performance and reduce costs. Use the Intelligent-Tiering storage class to further optimize costs on actively queried data. Gain operational visibility with granular metrics in CloudWatch, and logs in CloudTrail for storage, requests, and maintenance operations.
Advanced analytics
Access advanced Iceberg analytics capabilities and query data using familiar Amazon Web Services services like Amazon Athena, Redshift, and EMR through the S3 Tables integration with Amazon Glue Data Catalog. Additionally, you can use Iceberg REST compatible third-party applications like Apache Spark, Apache Flink, Trino, DuckDB, and PyIceberg, to read and write data into S3 Tables.
Simplified security
Manage tables as first-class Amazon Web Services resources with IAM resource policies for table-level access control. Use tags for attribute-based access control (ABAC) to streamline permissions management at scale. Secure data with Amazon KMS encryption using customer-managed keys to maintain control over your encryption strategy.
How it works
S3 Tables provide purpose-built S3 storage for storing structured data in the Apache Iceberg format. Within a table bucket, you can create tables as first-class resources directly in S3. These tables can be secured with table-level permissions defined in either identity- or resource-based policies and are accessible by applications or tooling that supports the Apache Iceberg standard. When you create a table in your table bucket, S3 maintains the metadata necessary to make that data queryable by your applications. Table buckets include an Iceberg REST catalog endpoint that can be used by any Iceberg-compatible query engines to discover, access, and update Iceberg metadata for tables in your table bucket. This allows for multiple clients to safely read and write data to your tables. Over time, S3 automatically optimizes the underlying data by rewriting, or "compacting” your objects. Compaction optimizes your data on S3 to improve query performance. Additionally, snapshot expiration and unreferenced file removal optimize storage cost as the data in your tables age. Read the user guide to learn more.