Learn
ETL vs. ELT: What's the Difference?
Both move and reshape data. The difference is when the transformation happens — before loading, or after.
The order of operations
ETL transforms data in-flight, before it's written to its destination. ELT loads raw data first, then relies on the destination system's own compute to transform it — typically a cloud warehouse like Snowflake or BigQuery.
Why the distinction emerged
ELT became a popular pattern as cloud warehouses made large-scale, on-demand SQL transformation cheap. Instead of transforming before loading, teams could load everything and reshape it later, as needed, using the warehouse itself.
Where DataQloo fits
DataQloo's workflow nodes — Filter, Summarize, Sort — transform data as part of building the workflow, against a live PostgreSQL connection or an imported dataset, and results are saved to DataQloo's own storage via an Output node. Writing raw, untransformed data into a separate warehouse for later transformation isn't part of DataQloo's current model.
See also: What Is ETL?
Frequently asked questions
In ETL, data is transformed before it's loaded into the destination. In ELT, raw data is loaded first, then transformed inside the destination system (often a warehouse with strong compute power).
See DataQloo’s Visual Designer for yourself.