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Comment by iamsomewalrus

:this: A concept that's underlying the move to a datalake architecture (read: keeping your data in its rawest form, and its transforms in S3 or HDFS) is decoupling your compute from storage.

Motivating example: you have huge tables in Redshift that are either infrequently accessed or the usefulness of the data decays over time (website logs, customer order information). In this scenario you're paying a lot just to keep data in Redshift (storage) but a large subset of the data is laying dormant (no compute).

If you're bought into the Redshift ecosystem this is where Redshift Spectrum comes in. If you're a smaller company you could just store the data in S3 and "spin up" the compute when you need it (Athena, Glue jobs, or Elastic Map Reduce clusters).

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