Using the ETL Tool for Data Migration in AWS

Among the many services provided by the cloud-based platform AWS (Amazon Web Service) is the migration of data between relational databases, data warehouses, and NoSQL databases. And one of the most optimized tools for doing so is ETL in AWS.


ETL is short for Extract, Transform, Load and is primarily used to combine several sources of data into a single data warehouse. In ETL in AWS, data is first extracted from the source, then transformed to match the data architecture of the target database, and finally loaded into the intended location which is a data warehouse or other storage repository.

There are several benefits of using ETL in AWSfor database migration.

First, there is no need to install and configure additional drivers and applications for database migration nor should the structure of the source database be changed. This is because migration with ETL in AWSis started directly through the AWS Management Console. All changes to the data at the source are replicated to the target database at regular and pre-determined intervals through the Change Data Capture (CDC) feature. However, this can only happen when both the source and the target databases are continually kept in sync.

An advantage for organizations when migrating databases with ETL in AWS is that the process can take place even when the source database is functional. This is a great help for large data-driven businesses for whom downtime even for the brief migration periods can upset operating schedules.

For migrating on-premises databases to Amazon RDS or Amazon EC2, Aurora, and databases running on EC2 to RDS or vice versa, ETL in AWS is the most preferred tool. 

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