Amazon SageMaker Feature Store Adds Support for Python SDK V3 and Enhanced Access Controls

SageMaker Feature Store integrated SageMaker Python SDK v3, offering modular interfaces with Lake Formation and Apache Iceberg support for improved feature data governance and storage optimization.

By Elena Parker · Editorial pseudonym · 2026-05-12 · 1 min read

AI-ASSISTED REPORTING · RETROSPECTIVE ARCHIVE

Retrospective edition: 2026-05-12. Source published: 2026-05-12. Added to this archive: 2026-11-03. This briefing was prepared later from the linked announcement; it was not published on this website on the historical edition date.

The new SDK v3 enables streamlined management of feature groups, reducing boilerplate code for data scientists. Integration with Lake Formation allows enforcing fine-grained access controls on offline store data at creation time, ensuring secure data sharing.

Support for Apache Iceberg table properties lets users configure compaction and snapshot expiration to optimize storage and query performance. These unified capabilities help machine learning teams govern and accelerate feature data management using a single SDK across AWS regions.

Source & further reading

Amazon SageMaker Feature Store now supports SageMaker Python SDK V3 ↗

Source published 2026-05-12. This report was prepared with AI assistance from the linked primary-source material. Claims and limitations should be checked against the original announcement or research.