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Simplify data lakes at scale with Amazon S3 Tables

Simplify data lakes at scale with Amazon S3 Tables

This session introduces Amazon S3 Tables, a new storage solution designed for efficient management of structured data at scale. Traditional approaches to handling tabular data often involve complex and costly systems for governance, maintenance, and optimization. S3 Tables aims to simplify these processes by offering streamlined table-level access control and automating key management tasks. These include data compaction, snapshot management, and ongoing query performance optimization.

Ibrahim Emara
Amazon Employee
Published Mar 25, 2025
The show featured Anupriti and Phaneendra discussing Amazon S3 Tables, a new storage solution for tabular data using the Apache Iceberg format. The feature aims to simplify data lake management by providing advanced capabilities such as schema evolution, time travel, and improved performance for analytical workloads.
S3 Tables introduces a new bucket type specifically designed for storing structured data with enhanced features. The Apache Iceberg format allows for flexible schema changes, snapshot management, and transactional capabilities without requiring full data rewrites. The solution integrates seamlessly with AWS analytics services like Athena, Lake Formation, and Amazon Data Firehose, enabling easy data ingestion and querying across multiple use cases in financial services, advertising technology, and IoT platforms.
The demonstration showcased the ease of creating S3 Table buckets, namespaces, and tables, and highlighted the integration with Amazon Data Firehose for streaming data ingestion. The solution offers automatic maintenance features like snapshot expiration, unreferenced file cleanup, and file compaction, while providing granular access controls through Lake Formation.

Show Highlights:

  • Purpose-built storage for tabular data using Apache Iceberg format
  • Supports schema evolution without full data rewrites
  • Enables time travel and snapshot management
  • Automatic file compaction and maintenance
  • Integrates with AWS analytics services
  • Supports multiple use cases (financial, IoT, advertising)
  • Seamless data ingestion through Amazon Data Firehose
  • Offers table-level and namespace-level permissions

Hosts of the show 🎤

Ibrahim Emara - Database Specialist SA @AWS

Guests 🎤

Anupriti Warade, Senior Product Manager @ 𝐀𝐖𝐒
Phaneendra Vuliyaragoli, Senior Product Manager @ 𝐀𝐖𝐒

Links from today's episode:

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