ETL is hard and outdated

  • ETL is expensive to implement, especially for small and medium businesses.
  • ETL is expensive to maintain.
  • ETL eliminates access to raw data.
  • ETL is time consuming. Users have to wait for transformation to be finished.

Why have we been doing it for decades?

  • Optimized for analytical operations. Modern analytical warehouses tend to be columnar and optimized for aggregating and processing huge datasets.
  • Cheap storage. No worries about what to store, you can just dump all your raw data into a warehouse.
  • Cloud based. It scales infinitely and on-demand, so you can get the performance you need the moment you need it.

ETL vs ELT: running transformations in a data warehouse



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