‫Next type of database we have is Redshift.
‫Redshift is a database that is based on PostgreSQL,
‫but it is not used for OLTP.
‫OLTP stands for Online Transaction Processing.
‫That is what RDS was good for.
‫Instead, Redshift is OLAP or Online Analytical Processing,
‫which is used to do analytics and data warehousing.
‫So anytime in the exam you are seeing the database needs
‫to be a warehouse and to do analytics on it,
‫then Redshift is going to be your answer.
‫With Redshift, you do not load data continuously,
‫you load it for example, every hour.
‫The idea with Redshift that it is really,
‫really good at analyzing data and making some computations.
‫So it boasts 10x better performance
‫than other data warehouses, and scales to petabytes of data.
‫The data is stored in columns.
‫So it is called a columnar storage
‫of data instead of a row based.
‫So anytime you see columnar again,
‫think Redshift and it has something
‫called the Massively Parallel Query Execution, MBP engine
‫to do these competitions very, very quickly.
‫It is pay as you go,
‫based on the instances you have provisioned
‫and has a SQL interface to perform the queries.
‫It is also finally integrated with BI.
‫So Business Intelligence tools such as Quicksight
‫or Tableau, if you want to create dashboards
‫on top of your data and your data warehouse.
‫So that is it.
‫Just a high level overview, that a data warehouse is used
‫to do some computation on your datasets
‫and do some analytics and possibly build
‫some visualizations through dashboards on it.
‫So for that use case, Redshift will be perfect.
‫So that is it for this lecture.
‫I hope you liked it,
‫and I will see you in the next lecture.