When this stack beats the alternative

Picking the lakehouse over a pure warehouse is a real tradeoff. You get cheaper storage and engine flexibility. You take on Iceberg setup, IAM complexity, and the operational overhead of two systems. The course makes the case where the tradeoff wins, and the case where it does not.

When this stack wins: high storage volume relative to query volume, multiple engines reading the same data (Snowflake plus Athena plus Spark), strict storage cost discipline, governance-led teams that want a single S3 source of truth.

When it loses: small datasets where storage cost is rounding error, a team that only ever queries with Snowflake, low-query-volume warehouses where the catalog overhead matters more than storage savings, or a strict regulatory environment where a single managed warehouse is required.

Same architecture, different vendor. Delta Lake is a table format, Unity Catalog is the catalog, Databricks runtime is the writer. Iceberg plus Glue plus Snowflake is more vendor-neutral. Pick by which engines your team actually uses. The patterns transfer.