Category: AWS Glue

Most of the cost of adopting something new isn’t the new thing, it’s the move. Moving a Hive table to Apache Iceberg has typically meant weeks of engineering work. Last week, Amazon S3 Tables turned that into three steps: start, sync as often as you need, complete. The source stays writable except for a few […]

You can now migrate existing Apache Hive datasets in Amazon S3 to fully managed Apache Iceberg tables in Amazon S3 Tables, with no pipelines to build or compute to provision, while production workloads keep running.

Some numbers are hard to picture until you sit with them for a moment. Last week we published the Prime Day 2026 metrics, and the one that stuck with me is 2.3 quadrillion: the daily requests Amazon ElastiCache peaked at during the event. Prime Day ran back in June, so this post always lands as […]

During my time at AWS, I have always looked for opportunities to work with students. I have delivered over 50 talks at universities across the region, and watching the potential in the room is always a strong motivator. It reminds me of why I do this work, and that the students I meet today may […]

AWS Glue 6.0 is built on a fully modernized runtime, Apache Spark 4.1, Python 3.13, and Scala 2.13, delivering 30% lower pricing than previous AWS Glue versions.

Access FSx for NetApp ONTAP file data through S3 to enable AI/ML workloads and analytics—letting you use enterprise file data with Bedrock, SageMaker, and analytics services while it remains in your file system.

Amazon S3 now enables improved Apache Iceberg query performance through two new compaction strategies—sort and z-order—available for both S3 Tables and general purpose S3 buckets, helping organize data more efficiently by clustering similar values together and reducing file scanning during queries.

Simplify data replication and ingestion from applications such as Salesforce, SAP, ServiceNow, and Zendesk, to Amazon SageMaker Lakehouse and Amazon Redshift.