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‫Next type of database we have is Redshift.

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‫Redshift is a database that is based on PostgreSQL,

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‫but it is not used for OLTP.

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‫OLTP stands for Online Transaction Processing.

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‫That is what RDS was good for.

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‫Instead, Redshift is OLAP or Online Analytical Processing,

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‫which is used to do analytics and data warehousing.

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‫So anytime in the exam you are seeing the database needs

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‫to be a warehouse and to do analytics on it,

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‫then Redshift is going to be your answer.

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‫With Redshift, you do not load data continuously,

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‫you load it for example, every hour.

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‫The idea with Redshift that it is really,

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‫really good at analyzing data and making some computations.

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‫So it boasts 10x better performance

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‫than other data warehouses, and scales to petabytes of data.

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‫The data is stored in columns.

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‫So it is called a columnar storage

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‫of data instead of a row based.

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‫So anytime you see columnar again,

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‫think Redshift and it has something

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‫called the Massively Parallel Query Execution, MBP engine

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‫to do these competitions very, very quickly.

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‫It is pay as you go,

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‫based on the instances you have provisioned

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‫and has a SQL interface to perform the queries.

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‫It is also finally integrated with BI.

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‫So Business Intelligence tools such as Quicksight

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‫or Tableau, if you want to create dashboards

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‫on top of your data and your data warehouse.

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‫So that is it.

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‫Just a high level overview, that a data warehouse is used

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‫to do some computation on your datasets

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‫and do some analytics and possibly build

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‫some visualizations through dashboards on it.

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‫So for that use case, Redshift will be perfect.

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‫So that is it for this lecture.

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‫I hope you liked it,

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‫and I will see you in the next lecture.