Data Architecture for ML: Lakes, Warehouses, Catalogs

The architecture questions behind Domain 1: lake versus warehouse, Glue Data Catalog and Lake Formation, partitioning and storage-cost strategy, and moving data in at scale.

Content current as of 2026-10.

Lessons

  1. Lake, warehouse, or both
  2. Catalogs and Lake Formation
  3. Partitioning, lifecycle, and storage cost
  4. DataSync, Storage Gateway, and getting data in

Sources