Migration to the cloud is one of the major imperatives for enterprises all over the world in present times.  Many businesses are shifting their legacy systems and infrastructure to the cloud for leveraging the power of resource efficiency. Therefore, the demand for various public cloud platforms such as AWS is increasing considerably, especially as businesses learn the benefits of the cloud.

One of the prominent concerns for enterprises in shifting to the cloud is the migration of databases. However, you can ensure seamless and efficient data migration using AWS DMS. The database migration service (DMS) of AWS is one of the formidable alternatives that can help you deal with the anxiety related to the shifting of a traditional database.

For example, loss of data during database migration can lead to issues for application downtime. So, it is highly essential to understand the use cases of AWS DMS, involving database migration for tackling these issues with ease.

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The following discussion would present some notable use cases of data migration using AWS DMS. Readers could identify credible insights regarding the practical implementation of AWS DMS for data migration to the cloud. One of the important factors in the following discussion is the reflection on specific use cases in database migration.    

What is AWS DMS?

Before starting our discussion on use cases for data migration using AWS DMS, it is essential to get a brief impression of the definition of AWS DMS. The AWS Database Migration Service (DMS) provides a fully managed cloud service for easier migration of relational databases, NoSQL databases, data warehouses, and various types of data stores.

AWS DMS can help you in the migration of your data to the AWS Cloud, between the combinations of on-premises and cloud setups, or between on-premise instances by leveraging an AWS Cloud setup. Users can easily replicate ongoing modifications for maintaining synchronization of sources and targets as well as perform one-time integrations easily.

Read full introduction to AWS Database Migration Service (AWS DMS) here: https://www.whizlabs.com/blog/aws-database-migration-service/

You can opt for the AWS Schema Conversion Tool for the translation of existing database schema to the concerned new platform. The AWS SCT is ideal for scenarios where you want to switch database engines before migrating data using the AWS DMS.

Data migration using AWS DMS also ensures the benefits of better flexibility, security, cost-effectiveness, and faster speed to market, which come with all AWS services. You can explore the basics of AWS DMS further to dive deeper into its architecture, working, and benefits for enterprises.

However, our primary objective in this discussion is to outline the specific use cases of the AWS database migration service. So, with the basic impression of AWS DMS, let’s start reflecting on its various use cases.

General Data Migration Use Cases

One of the first things that we should look into for understanding the various use cases of AWS DMS is the outline of use cases for data migration.

  • Homogeneous Migration

The first use case in data migration refers to homogenous migrations. Homogenous migration is one of the conventional data migration options that involve transferring database instances that use the same database technology. Homogenous migrations need considerably extensive planning for ensuring compliance with the uptime SLAs. In addition, homogenous migrations also ensure a limited loss of data during the migration process.

  • Heterogeneous Migration

The next important data migration use case before reflecting on data migration using AWS DMS refers to heterogeneous migrations. Heterogeneous migrations clearly imply the migration of database instances from one database technology to another. For example, a team migrating from MySQL to SQL Server showcases a heterogeneous migration process.

Although the reasons for heterogeneous migrations can vary considerably from one enterprise to another, there were many challenges accompanying them. One of the critical challenges associated with heterogeneous migrations is the support for data types across different platforms.

  • Migration from On-Premises to Cloud

The final data migration use case refers to the migration of data from on-premises databases to the Cloud. This is practically the most sought after type of database migration approaches that enterprises face currently.

However, the most critical challenge, in this case, refers to the fact that database services on the cloud such as Redshift or RDS do not have every technology feature that users are familiar with in a native SQL Server environment.

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Use Cases of AWS DMS Data Migration

Now, let us take a look at the different use cases involving data migration using AWS DMS. We can reflect on the different implications of each use case with a reflection on the interaction between individual components.

  • Homogenous Database Migrations

Homogeneous database migrations, as discussed above, the source and target database engines are similar. In addition, the source and target database engines could be compatible with each other as follows.

  • MySQL to Amazon Aurora or Amazon RDS for MySQL.
  • Oracle to Amazon RDS for Oracle.
  • Microsoft SQL Server to Amazon RDS for SQL Server.

Homogenous migrations are generally one-step processes, because of the compatibility of schema structures, database code and data types between the source and target database. Users can create a migration task accompanying connections to source and target databases, before starting migration with a single click.

Once you have clicked on the mouse button, the AWS DMS takes care of the rest. Source database could be located on-premises external to AWS, running on an EC2 instance. The source database could also be an Amazon RDS database.

On the other hand, the target could be a database in Amazon RDS or Amazon EC2. Leading provider of innovative communications and technology solutions, Verizon, utilizes AWS DMS for effective identification of areas of data conversion.

  • Heterogeneous Database Migrations

The dissimilarity of source and target database engines is one of the foremost highlights of heterogeneous database migrations. For example, migrations of Oracle to Amazon Aurora, Microsoft SQL Server to MySQL or Oracle to PostgreSQL are heterogeneous migrations.

Heterogeneous data migration using AWS DMS requires a schema and code transformation process before starting the migration process. This is evidently necessary for addressing the dissimilarities between data types, database code, and schema structure of source and target databases. Therefore, heterogeneous migration processes are generally two-step processes.

As mentioned previously, in data migration use cases, the AWS Schema Conversion Tool can support helpful conversion of source schema and code for matching that in the target database. Following this step, you can use the AWS Database Migration Service for the migration of data from the source to the target database.

The use cases of AWS database migration service in heterogeneous migration would also help you uncover the fact that AWS DMS takes care of all data type conversions automatically. The target database could be in Amazon RDS or Amazon EC2. The location of the source database could be an Amazon RDS database or on-premises, external to AWS, and running on EC2 instance.

  • Development and Testing

Another prominent mention among use cases of data migration using AWS DMS refers to the migration of data into and outside of the cloud for the objectives of development. In such use cases, you can easily notice two distinct scenarios. One scenario involves deployment, development, testing, or staging systems on AWS.

Developers and testers can leverage AWS DMS for using copies of real production data to ensure the copying of updates back on the on-premises production system. The second scenario involves the presence of development systems in on-premises locations.

Users are opting for the migration of an existing copy of the AWS Cloud production database to the on-premises systems once or continuously. As a result, existing DevOps processes have limited disruptions while ensuring an updated representation of the production system.

  • Database Consolidation

Data migration using AWS DMS becomes better with the facility for the consolidation of multiple source databases into a specific target database. Database consolidation is possible for heterogeneous and homogeneous migrations as well as all applications for all supported database engines.

Apart from the recommended specifications for the source database for data migration, the source database could also be present across various locations for database consolidation.

  • Continuous Data Replication

Among the many use cases pertaining to data migration using AWS DMS, continuous data replication stands out distinctively. The use case of AWS DMS for continuous data replication would include important steps such as disaster recovery instance synchronization, dev/test environment synchronization, and geographic database distribution.

Users can ensure replication of data on a single database to one or multiple target databases. On the other hand, you can also consolidate multiple source databases and replicate them to one or multiple target databases.

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Final Words

The various use cases for data migration using AWS DMS presented here clearly showcase its efficiency. Apart from the general data migration tasks, AWS DMS supports database consolidation, development, and testing as well as continuous data replication functionalities. AWS DMS contains a host of various services that simplify data migration while bringing potentially favorable levels of flexibility.

The benefits of AWS DMS adequately complement its functionalities in delivering easier database management. For example, the cost-effectiveness and ease of installation that you can find with AWS DMS are very promising factors for database administrators. So, gradual practice and exploring different resources about AWS DMS can help us leverage its full potential for your benefits.

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