Amazon Redshift best practices

Following, you can find best practices for planning a proof of concept, designing tables, loading data into tables, and writing queries for Amazon Redshift, and also a discussion of working with Amazon Redshift Advisor.

Amazon Redshift is not the same as other SQL database systems. To fully realize the benefits of the Amazon Redshift architecture, you must specifically design, build, and load your tables to use massively parallel processing, columnar data storage, and columnar data compression. If your data loading and query execution times are longer than you expect, or longer than you want, you might be overlooking key information.

If you are an experienced SQL database developer, we strongly recommend that you review this topic before you begin developing your Amazon Redshift data warehouse.

If you are new to developing SQL databases, this topic is not the best place to start. We recommend that you begin by reading Run commands to define and use a database in your data warehouse in the Amazon Redshift Getting Started Guide, and trying the examples yourself.

In this topic, you can find an overview of the most important development principles, along with specific tips, examples, and best practices for implementing those principles. No single practice can apply to every application. Evaluate all of your options before finishing a database design. For more information, see Automatic table optimization, Loading data in Amazon Redshift, Query performance tuning, and the reference chapters.