21 December 2022 | Noor Khan

The AWS data migration service (DMS) is a service that enables organisations to move their data, quickly, efficiently and securely to AWS from a wide variety of data sources. AWS migration is a pay-as-you-go model and is known to help businesses minimise downtime during migration and avoid any data loss. It is used by some leading brands including Samsun and Melia Hotel and Resorts.
In this article, we will look at AWS data migration service in detail and how you can successfully migrate your data.
AWS DBS is just one of the many leading technologies in the AWS ecosystem and is becoming popular. The way AWS DMS works is that the data from the source is replicated and migrated to the pre-defined target destination. With AWS DMS, you have three data migration options and they are as follows:
Full Load – This type of data migration migrates your entire data set at a specific point and it does not replicate the data changer past that point. This is ideal for one-time data migrations.
Full Load + CDC – Full load and CDC data migration consist of migrating all existing data from the source point with replication and additionally replicating any subsequent changes to the data. This is ideal for ongoing data migration and if there are changes in the data.
CDC – CDC data migration is the ideal option if you are looking to replicate changes but not move the entire database. Organisations will adopt this type of migration if they are using an alternative method to migrating the main database.
There are several benefits of AWS DMS and they include:
Cost-effective – With a pay-as-you-go model, you only pay for what you use which makes it a cost-effective data migration solution.
Minimal downtime – With the replication you can minimise system downtime which can be a challenge for data migration projects
Homogeneous and heterogenous migrations – AWS DMS can be used for both types of data migrations.
Supports a wide number of database sources – This includes the likes of Oracle, MongoDB, MariaDB, PostgreSQL, and MySQL.
Security – AWS offer robust security for data at rest as well as data that is being migrated.
Failure and recovery – AWS DMS is built in with a backup replication server, which comes into play if there is a failure.
There are also some limitations to consider if you are looking to employ AWS DMS for your data migration and they include:
Schema and code conversion – If you want to migrate your schema, there are other tools offered by AWS which can be adopted such as AWS SCT.
No on-premise to on-premise migration – AWS DMS does not support the migration of data from one on-premise data source to another.
Only used with AWS – To use AWS DMS, one of the data endpoints have to be an AWS service such as AWS Aurora, S3 or Redshift.
Slow performance – If you are migrating large volumes it may slow down your systems, therefore may not be ideal for large-scale data migrations.
Migrating your data efficiently and within time and cost scale can be challenging. If your organisation does not have the skills, expertise or resource to carry out the migration with AWS DMS, then consider outsourcing. Outsourcing your data migration can offer several benefits including:
Ardent’s highly skilled data engineers have successfully completed many data migration solutions. We can migrate your data from one or many to your preferred data destination, whether you are looking to migrate from outdated legacy systems to the cloud or from one cloud solution to another. We are a certified AWS partner and have worked with a wide variety of leading AWS technologies to deliver data migration, including migrating data from Microsoft to AWS and from Oracle to AWS Redshift.
If you are looking to migrate your data in a cost and time-efficient way, we can help. Get in touch to find out more or to get started to unlock the potential of your data.
At Ardent, we have spent years helping organisations design, modernise and operate the data foundations behind critical reporting, analytics and decision-making. That experience gives us a clear view of what now separates AI-ready businesses from those still struggling to get value from their data. It is not the amount of data they hold, or even [...]
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