Amazon Web Service DMS (Database Migration Service) facilitates easy and seamless migration of databases. The advantage is that during migration, the source database remains fully functional and organizations do not have to opt for downtime.

Benefits of data migration to AWS.

•User-friendly: It is not necessary to install additional drivers or applications to the source database during data migration to AWS as the process can be started with just a few clicks on the AWS Management Console. The migration process is fully automated and DMS handles the entire activity by replicating the changes to the target database whenever they happen in the source database.

•Negligible downtime: Databases are migrated to AWS through DMS with almost negligible downtime. All changes that occur at the source are continually replicated to the target without break. Database administrators can keep the target database synchronized with the source database as long as it is needed for data migration to AWS.

•Database support: Data migration to AWS can be executed from the most common commercial and open-source databases. Both homogeneous migration and heterogeneous migrations are supported by AWS DMS. Migrations occur between on-premises databases to Amazon RDS or Amazon EC2, Aurora as well as databases running on EC2 to RDS or vice versa. This system can also move data between SQL, NoSQL and text-based data.

Because of these many benefits, organizations are increasingly opting for data migration to AWS.

Types of Data Migration to AWS

AWS DMS facilitates continuous data replication with high availability and can combine databases into petabyte-scale data warehouses by streaming data to Amazon Redshift and Amazon S3. When databases are being migrated to Amazon Aurora, Amazon Redshift, and Amazon DynamoDB, DMS can be used for free initially for six months.

There are two types of data migration to AWS.

•Homogeneous Database Migration: In this form of data migration to AWS, the source and the target database engines are the same and complement each other. It is a one-step process as the database code, the schema structure, and the data types are well-matched. Examples of this instance are Oracle to Amazon RDS for Oracle, MySQL to Amazon Aurora, MySQL to Amazon RDS for MySQL, or Microsoft SQL Server to Amazon RDS for SQL Server.

•Heterogeneous Database Migration: Here the source and the target database engines are different. Schema and code transformation are required before data migration to AWS as the schema structure, data type, and the database code of source and target databases are different. The first step is to use the AWS Schema Conversion Tool and convert the source code and schema to match that of the target database. Next, use the AWS DMS to migrate data from the source to the target database. Examples include Oracle to Amazon Aurora, Oracle to PostgreSQL, or Microsoft SQL Server to MySQL migrations.

These are the types and benefits of AWS Database Migration Service.