Axtria White Paper

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WHITEPAPER

Table Size Optimization for Small Datasets in Amazon Redshift

ABSTRACT

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

The factors which affect the performance and sizing of the Redshift environment are - Type and numbers of Nodes with slices, Distribution style, Compression, and 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 provide a recommendation to handle smaller datasets.

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