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Amazon S3 Tables now support all Apache Iceberg V3 data types

Amazon S3 Tables now support all data types in the Apache Iceberg V3 specification. The interesting part is that AI is edging closer to practical work, not just polished demos.

Amazon S3 Tables now support all data types in the Apache Iceberg V3 specification. You can create V3 tables or upgrade existing V2 tables to take advantage of V3 features like deletion vectors, row lineage, and new data types such as variant, nanosecond timestamps, unknown, geometry, and geography. The useful part sits in the context, the practical impact, and what readers can use to decide the next step.

Amazon S3 Tables now support all Apache Iceberg V3 data types

Amazon S3 Tables now support all data types in the Apache Iceberg V3 specification. You can create V3 tables or upgrade existing V2 tables to take advantage of V3 features like deletion vectors, row lineage, and new data types such as variant, nanosecond timestamps, unknown, geometry, and geography.

What changed

The floor is firmer here because the story is anchored by an official source, not only by second-hand reaction. For people paying for AI tools, the difference only matters when it removes real steps from writing, research, meetings, coding, or operations rather than adding another feature label.

Price and bundle value

Apache Iceberg has become the open standard for managing large analytics datasets. It lets you manage petabyte-scale tables with features like schema evolution, hidden partitioning, and time travel queries, while keeping your data in open Parquet files in data lakes on object storage like Amazon S3 . Amazon S3 Tables offer storage purpose-built to keep Iceberg tables performant and cost-effective as they grow, with fully managed features like automatic compaction, maintenance, replication, and Intelligent-Tiering.

AI features that change the value

Starting today, Amazon S3 Tables support all V3 data types, including variant, nanosecond timestamps, geometry, geography, and unknown, along with deletion vectors and row lineage. You can create new V3 tables or upgrade existing V2 tables in place, and S3 Tables continue to run compaction and maintenance for you. The readers who should look most closely are usually freelancers, content teams, product teams, and smaller businesses deciding which paid AI layer is actually worth it. Even once the story is verified, the useful follow-up is which company keeps practical value alive after the launch-day noise fades.

Who should pay attention

Apache Iceberg V3 V3 is the latest version of the Iceberg specification . Among its many improvements, V3 introduces capabilities that address the most common pain points in V2. This includes:. Even once the story is verified, the useful follow-up is which company keeps practical value alive after the launch-day noise fades. That is why the useful reading move is not to stop at the headline, but to compare the promise, the workflow change, and the likely cost before deciding anything.

Patrick Tech Media take

Deletion vectors replace V2’s positional delete files with a compact binary format. That 50,000-row compliance delete now writes a single deletion vector file instead of thousands of small deletes, significantly reducing compaction time and delete file overhead. That is why the useful reading move is not to stop at the headline, but to compare the promise, the workflow change, and the likely cost before deciding anything.

Source notes

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