For a small dataset like that, Redshift is overkill. Especially if it's a one time thing. Redshift excels when you have (at least) TBs of data from many differe

For a small dataset like that, Redshift is overkill. Especially if it's a one time thing. Redshift excels when you have (at least) TBs of data from many different sources. Having said that - if you expect to query your data on an ongoing basis, with fresh (and growing) data coming in every day, then it's worth considering. You can run your transformations on top of raw data in Redshift. It's certainly more expensive than S3. But with just a few GBs, you'll stay underneath $150 / months. Reg. Spark vs. Redshift - see my post on Quora: https://www.quora.com/Spark-vs-Redshift-Should-I-be-using-both-for-big-data-Which-is-better/answer/Lars-Kamp?srid=DtA https://www.quora.com/Spark-vs-Redshift-Should-I-be-using-bo...