Online systems tend to track user’s actions. Gathering information about users’ behavior can increase the quality of their experience, which can lead to increased business income. In this article, we will show how to reimplement an existing Postgres database to a more complex analytics database like Amazon Redshift. The solution we want to reengineer is a tracking system for an online SQL learning platform like LearnSQL.com. The source implementation is built on a PostgreSQL database and contains two main tables:
Find out how to design an Amazon Redshift schema in Vertabelo. Thanks to increasing volumes of data, analytical databases like Amazon Redshift are gaining market. We introduced Redshift support at the end of 2019; in this article, we will explain how to design a Redshift data model using Vertabelo. How to Create a Model Let's start with the data model creation process. To create a Redshift schema, please: Log into Vertabelo and click on Create new document.
Amazon Redshift is one of the most popular cloud databases. Could it be your data-warehouse solution? Read on to find out if Amazon Redshift meets your needs. In 2012, Amazon announced its new cloud database system called Redshift. Basically, it is a data-warehouse solution intended for analytical systems, which can handle huge volumes of data—up to 1 petabyte (1024 TB). Amazon Redshift is available as a service (Database as a Service) and is a part of a bigger cloud ecosystem called Amazon Web Services (AWS).