Its a bit confusing to claim that "The things your current stack can't give you because it doesn't own the DAG" and use DataBricks as your example: DataBricks includes jobs and pipelines, so it very much owns the DAG, no?

Fair point. Databricks owns a scheduling DAG (Workflows, DLT). What I meant by "owns the DAG" is the semantic DAG: model-to-model dependencies with column-level types that the compiler builds.

Workflows knows task A runs before task B. Rocky knows `dim_customer.email` flows from `raw_users.email_address` through three CTEs in `stg_customers`. Different layer, same word.

I'll be more careful with that framing.