Create a Schema Conversion Project

Now that you have installed the AWS Schema Conversion Tool, the next step is to create a Database Migration Project using the tool.

Specify the source database

1. Within the Schema Conversion Tool, if the new project wizard doesn’t start please start it by going to File > New Project Wizard top left corner. Once in Project wizard mode, please enter the following values into the form note you’ll need to adjust for the source database you selected in the text below and then click Next.

   Parameter	Value
   Project Name	AWS Schema Conversion Tool Source DB to Aurora MySQL (or Aurora PostgresSQL)
   Location	C:\Users\Administrator\AWS Schema Conversion Tool
   Type Radio Button	Click/Select SQL Database
   Source Database Engine	Microsoft SQL Server, Oracle or Source you selected earlier in this session
   “I want to” Radio Button	Click/Select I want to switch engines and optimize for the cloud

   

   

2. Specify the source database configurations in the form, Please note the password is not provided below you need to goto Secrets Manager and open DMSDBSecret and reveal the SQLServer password value. It is also on first Cloudformation Stack’s output tab (SQLServerPassword) and click Test Connection. Once the connection is successfully tested, click Next.

   Depending on your source database, choose one of the following routes to follow the steps.

   Oracle Source Information

   Expand to see

   Parameter	Value
   Connection Name (if there)	Oracle Source
   Type	SID
   Server Name	< SourceOracleEndpoint (you can find this in Cloudformation Output tab or goto RDS service in
   Server Port	1521
   Oracle SID	ORACLEDB
   User Name	dbadmin
   Password	See Cloudformation Output tab & DMSDBSecretP or look it up in AWS Secrets Manager for Oracle
   Use SSL	Unchecked
   Store Password	Checked
   Oracle Driver Path	C:\Users\Administrator\Desktop\DMS Workshop\JDBC\ojdbc11.jar

   MS SQL Server Source Information

   Expand to see

   Parameter	Value
   Connection Name (if there)	SQL Server Source
   Project Name	localhost
   Server Port	1433
   Instance Name	localhost
   Authentication	SQL Server Authentication
   User Name	dbadmin
   Password	See Cloudformation Output tab & DMSDBSecretPSQLSERVER or look it up in AWS Secrets Manager for SQL Server
   Use SSL	Unchecked
   Store Password	Checked
   Microsoft SQL Server Driver Path	C:\Users\Administrator\Desktop\DMS Workshop\JDBC\mssql-jdbc-12.6.1.jre11.jar

   

3. Select the dms_sample database, then click Next. (Note: once you click on database gray/blue bar highlight should appear & Next button will be enabled)

   

Review the Database Migration Assessment Report.

1. SCT will examine in detail all of the objects in the schema of source database. It will convert as much as possible automatically and provides detailed information about items it could not convert. If you scroll down on the report you’ll see specific target databases like below for SQL Server to Aurora MySQL.

   Generally, packages, procedures, and functions are more likely to have some issues to resolve because they contain the most custom or proprietary SQL code. AWS SCT specifies how much manual change is needed to convert each object type. It also provides hints about how to adapt these objects to the target schema successfully.

2. After you are done reviewing the database migration assessment report, click Next.

   

Specify the target database

Specify the target database configurations in the form, Please note the password is not provided below you need to go to Secrets Manager and open DMSDBSecret and reveal the password. It is also on first Cloudformation Stack’s output tab see the SQLSever password (same as above) and then click Test Connection. Once the connection is successfully tested, click Finish.