Thanks for these links! We consider ourselves an ELT and ETL tool—if you run a Serra job in your own warehouse (ie Databricks), you can easily specify extracting from AWS, loading the parquets into your warehouse, then transforming them with our config block approach (ELT).
The same is true for ETL. If you have a spark cluster separate from your warehouse, you can define your config file to run in the order E T L: you can extract from your data source, run the transformations on a separate cluster, then load it to your warehouse.
The same is true for ETL. If you have a spark cluster separate from your warehouse, you can define your config file to run in the order E T L: you can extract from your data source, run the transformations on a separate cluster, then load it to your warehouse.