Suppose in a raw unstructured data coming in from various sources such as a csv files or databases. AWS takes this data clean it and save it int the appropriate format into a target database or data warehouse.
For example just as a raw material enter a factory where a machine clean it, transformed it into a finished product and pack it into a box Glue perform that very same function of cleaning and packing.
Amazon EMR (Spark / Hadoop)
It is used for big data processing when the data is so large that it can not be handled by a standard computer or server.
It uses the Apache Spark or Hadoop framework to process large dataset rapidly by distributing the workload across thousand of computer or cluster.
For example imagine if you had to analyze data for a building people a single computer would takes year to complete the task. EMR however create a teams means a clusters of computers that work together to accomplish a massive jobs in just a few minutes.
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Amazon Redshift (Data Warehousing)
This is the superfast data warehouse where you store all your businesses data in one place and run complex query or business dashboard on it.
It uses column based storage which allow data consisting of billions of rows to be search and analyze in second.
For example think of it like a large company central locker or warehouse where all sales record and customer details from the past 10 years are kept safely so that with just a single click the boss can view a report showing a profit made that year.
AWS DMS (Database Migration Service)
This is a tool used for migrating or transferring database from one location to another.
You can migrate data from your existing on-premises database or a cloud database to the cloud without any downtime without having to shutdown your application.
For example it’s like you old house(Database) becoming too small so you are moving all your belonging without any loss into a new large house(AWS cloud) all while your daily operation continue uninterrupted during the transition.
