What is the AWS Schema Conversion Tool? - AWS Schema Conversion Tool

What is the AWS Schema Conversion Tool?

You can use the AWS Schema Conversion Tool (AWS SCT) to convert your existing database schema from one database engine to another. You can convert relational OLTP schema, or data warehouse schema. Your converted schema is suitable for an Amazon Relational Database Service (Amazon RDS) MySQL, MariaDB, Oracle, SQL Server, PostgreSQL DB, an Amazon Aurora DB cluster, or an Amazon Redshift cluster. The converted schema can also be used with a database on an Amazon EC2 instance or stored as data on an Amazon S3 bucket.

AWS SCT supports several industry standards, including Federal Information Processing Standards (FIPS), for connections to an Amazon S3 bucket or another AWS resource. AWS SCT is also compliant with Federal Risk and Authorization Management Program (FedRAMP). For details about AWS and compliance efforts, see AWS services in scope by compliance program.

AWS SCT supports the following OLTP conversions.

Source database Target database

IBM Db2 LUW (versions 9.1, 9.5, 9.7, 10.5, 11.1, and 11.5)

Amazon Aurora MySQL-Compatible Edition (Aurora MySQL), Amazon Aurora PostgreSQL-Compatible Edition (Aurora PostgreSQL), MariaDB 10.5, MySQL, PostgreSQL

For more information, see Using IBM Db2 LUW as a source for AWS SCT.

Microsoft Azure SQL Database

Aurora MySQL, Aurora PostgreSQL, MySQL, PostgreSQL

Microsoft SQL Server (version 2008 R2 and later)

Aurora MySQL, Aurora PostgreSQL, Babelfish for Aurora PostgreSQL (only for assessment reports), MariaDB 10.5, Microsoft SQL Server, MySQL, PostgreSQL

For more information, see Using Microsoft SQL Server as a source for AWS SCT.

MySQL (version 5.5 and later)

Aurora PostgreSQL, MySQL, PostgreSQL

For more information, see Using MySQL as a source for AWS SCT

You can migrate schema and data from MySQL to an Aurora MySQL DB cluster without using AWS SCT. For more information, see Migrating data to an Amazon Aurora DB cluster.

Oracle (version 10.2 and later)

Aurora MySQL, Aurora PostgreSQL, MariaDB 10.5, MySQL, Oracle, PostgreSQL

For more information, see Using Oracle Database as a source for AWS SCT.

PostgreSQL (version 9.1 and later)

Aurora MySQL, Aurora PostgreSQL, MySQL, PostgreSQL

For more information, see Using PostgreSQL as a source for AWS SCT.

SAP ASE (12.5, 15.0, 15.5, 15.7, and 16.0)

Aurora MySQL, Aurora PostgreSQL, MariaDB 10.5, MySQL, PostgreSQL

For more information, see Using SAP ASE (Sybase ASE) as a source for AWS SCT.

AWS SCT supports the following data warehouse conversions.

Source data warehouse Target data warehouse

Amazon Redshift

Amazon Redshift

For more information, see Using Amazon Redshift as a source for AWS SCT.

Azure Synapse Analytics (version 10)

Amazon Redshift

Greenplum Database (version 4.3 and later)

Amazon Redshift

For more information, see Using Greenplum Database as a source for AWS SCT.

Microsoft SQL Server (version 2008 and later)

Amazon Redshift

For more information, see Using Microsoft SQL Server Data Warehouse as a source for AWS SCT.

Netezza (version 7.0.3 and later)

Amazon Redshift

For more information, see Using Netezza as a source for AWS SCT.

Oracle (version 10.2 and later)

Amazon Redshift

For more information, see Using Oracle Data Warehouse as a source for AWS SCT.

Teradata (version 13 and later)

Amazon Redshift

For more information, see Using Teradata as a source for AWS SCT.

Vertica (version 7.2 and later)

Amazon Redshift

For more information, see Using Vertica as a source for AWS SCT.

Snowflake (version 3)

Amazon Redshift

For more information, see Using Snowflake as a source for AWS SCT.

AWS SCT supports the following data NoSQL database conversions.

Source database Target database

Apache Cassandra (versions 2.1.0, 2.1.20, and 3.11.4)

Amazon DynamoDB

Schema conversion overview

AWS SCT provides a project-based user interface to automatically convert the database schema of your source database into a format compatible with your target Amazon RDS instance. If schema from your source database can't be converted automatically, AWS SCT provides guidance on how you can create equivalent schema in your target Amazon RDS database.

For information about how to install AWS SCT, see Installing, verifying, and updating AWS SCT.

For an introduction to the AWS SCT user interface, see Using the AWS SCT user interface.

For information on the conversion process, see Converting database schemas using the AWS SCT.

In addition to converting your existing database schema from one database engine to another, AWS SCT has some additional features that help you move your data and applications to the AWS Cloud:

  • You can use data extraction agents to extract data from your data warehouse to prepare to migrate it to Amazon Redshift. To manage the data extraction agents, you can use AWS SCT. For more information, see Using data extraction agents.

  • You can use AWS SCT to create AWS DMS endpoints and tasks. You can run and monitor these tasks from AWS SCT. For more information, see Using AWS SCT with AWS DMS.

  • In some cases, database features can't be converted to equivalent Amazon RDS or Amazon Redshift features. The AWS SCT extension pack wizard can help you install AWS Lambda functions and Python libraries to emulate the features that can't be converted. For more information, see Using the AWS SCT extension pack.

  • You can use AWS SCT to optimize your existing Amazon Redshift database. AWS SCT recommends sort keys and distribution keys to optimize your database. For more information, see Optimizing Amazon Redshift by using the AWS SCT.

  • You can use AWS SCT to copy your existing on-premises database schema to an Amazon RDS DB instance running the same engine. You can use this feature to analyze potential cost savings of moving to the cloud and of changing your license type.

  • You can use AWS SCT to convert SQL in your C++, C#, Java, or other application code. You can view, analyze, edit, and save the converted SQL code. For more information, see Converting application SQL using the AWS SCT.

  • You can use AWS SCT to migrate extraction, transformation, and load (ETL) processes. For more information, see Converting ETL processes to AWS Glue.

Providing feedback

You can provide feedback about the AWS SCT. You can file a bug report, submit a feature request, or provide general information.

To provide feedback about AWS SCT

  1. Start the AWS Schema Conversion Tool.

  2. Open the Help menu and then choose Leave Feedback. The Leave Feedback dialog box appears.

  3. For Area, choose Information, Bug report, or Feature request.

  4. For Source database, choose your source database. Choose Any if your feedback is not specific to a particular database.

  5. For Target database, choose your target database. Choose Any if your feedback is not specific to a particular database.

  6. For Title, type a title for your feedback.

  7. For Message, type your feedback.

  8. Choose Send to submit your feedback.