On December 20 2016, Amazon released version 1.0.502 of AWS Schema Conversion Tool (SCT). SCT now provides the integration with Data Migration Service (DMS) and allows you to create AWS DMS endpoints and tasks. In addition SCT allows you to run and monitor the DMS tasks from SCT.
AWS Database Migration Service helps you migrate databases to AWS easily and securely. The AWS Database Migration Service can migrate your data to and from most widely used commercial and open-source databases. The service supports homogenous migrations such as Oracle to Oracle, as well as heterogeneous migrations between different database platforms, such as Oracle to Amazon Aurora or Microsoft SQL Server to MySQL.
As part of DMS integration, SCT introduced support for AWS profiles where users can store credentials for Amazon S3, AWS Lambda and DMS using the AWS Schema Conversion Tool interface. Finally, SCT now supports Amazon Aurora with PostgreSQL as a target database for conversion and migration projects.
In order to use Data Migration Services inside the AWS Schema Conversion Tool, you must specify the required credentials. You can store the credentials in the corresponding Service Profile, which can be set up in the general application settings. To do so, click the Settings button, choose Global Settings, and go to the AWS Service Profiles tab.
To set up the service profile, you have to specify its name, AWS Access and Secret keys, and the region. After the setup is completed, press the Save button.
Preparing Data Migration
A typical database migration project usually consists of 12 basic steps. So, now the AWS Schema Conversion Tool to some extent (we mean fully or partially) covers the following steps described in our methodology:
- Database schema conversion;
- Application conversion / remediation;
- Scripts conversion;
- Data migration.
Before you can actually use the Data Migration Service, integrated into the Schema Conversion Tool, there are a few things that you need to address. First, you have to establish a connection to the source and target databases. Then you must convert schemas and apply them to the target database. This step is needed since DMS expects the tables to exist in the target database.
Using Data Migration Service
When this is done, you can move forward to creating a DMS task. To do so, just select the objects to migrate data from the source metadata tree and click Actions — Create DMS task. Also, this option can be chosen from a pop-up menu after you right-click on selected objects.
On the next step, you must specify the needed parameters to start the data migration process. They are the task name, the replication instance, and the source and target endpoints. Also, you can include or exclude the LOB columns, and enable logging for the operation.
When everything is set and the endpoints are created, just press the Create button. You will get to the Data Migration View window.
SCT puts the data migration task into the queue, however you still have to launch it manually.
You can track its progress in the Data Migration View or switch back to your SCT project.
When the data load is completed, we use Database Compare Suite to compare the tables in source and target databases.
As you can see, SCT completed the data migration operation successfully.
Summarizing all features implemented in the new version of the AWS SCT, we can see that the tool is not only getting new features, but it is also becoming more user-friendly and intuitive. The expected and long-awaited update of AWS Schema Conversion Tool brings integration of Data Migration Service for OLTP databases. Now you can perform and control all operations of an OLTP database migration project in one application — you don’t need to switch to another window anymore. For a complete overview of the new capability from AWS, check out Working with the AWS Database Migration Service Using the AWS Schema Conversion Tool.
Be sure to check out our new AWS Schema Conversion Tool Jumpstart offer to get you up and running fast for your AWS database migration projects.
Related AWS SCT Posts
- Migrating an Oracle to MySQL Database using the AWS Schema Conversion Tool
- AWS Schema Conversion Tool: Offline mode
- AWS Schema Conversion Tool: Connecting to Oracle Source Database
- Selecting target database type for migration using Assessment Report in AWS Schema Conversion Tool
- Troubleshooting database migration issues using AWS Schema Conversion Tool Assessment Report
- Converting Objects during Database Migration using AWS Schema Conversion Tool
- Applying Converted Code to Target Database
- General Approach to Migration of Data Warehouses to Amazon Redshift
- Specific Features of Migrating Data Warehouses to Redshift
- Using AWS Schema Conversion Tool for Application Conversion
- Optimizing your Redshift Storage with AWS Schema Conversion Tool
- Extracting Data from Warehouses with Data Migration Agents in AWS Schema Conversion Tool
- Using AWS Schema Conversion Tool Extension Pack for OLTP databases
- Using AWS Schema Conversion Tool Extension Pack for Data Warehouses