ETL: dumb data warehouse. You do your own transform before inserting the data.

ELT: smart data warehouse. You dump the raw data and transform in the data warehouse later.

Or, DWH is just storage vs DWH is storage + transform.

When I built a ETL pipeline before the term ELT existed, we had multiple pipelines that transformed data in the data warehouse as well as transforms of the raw data on the way in. The transforms on the "way" in were minor like renames or formats while the transforms from within the dwh were much more involved.

Every pipe from db to dw is going to be some form of ETL, it's just that with "raw" data the transform is minimal. Unless your going apples-to-apples data storage, there's going to be some transforms in the actual underlying data types.

I agree with a comment down below, it's a genius marketing term.

> we had multiple pipelines that transformed data in the data warehouse

I've done this in the past too. But that isn't simply what ELT is. In the past compute was tied to storage which made these transforms interfere with load on the actual system.