Table Size Optimization For Small Datasets In Amazon Redshift

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse, but to make it cost-efficient, one needs to be aware of some key factors that affect the table sizing and eventually performance. This paper highlights those nuances and also explains how to deal with the smaller datasets in the mix of massive datasets.

The factors that affect the performance and sizing of the Redshift environment are the type and numbers of Nodes with slices, Distribution style, Compression, Vacuum strategy, etc. Redshift also provides out-of-the-box settings for these, but it is tuned for large datasets. This paper explains each scenario with the help of use cases and also provides a recommendation to handle smaller datasets.

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