AWS database schema conversion options
AWS offers two schema conversion solutions to make heterogeneous database migrations predictable, fast, secure, and simple. Customers have the choice to: 1) log in to the AWS Database Migration Service (AWS DMS) console to initiate the AWS DMS Schema Conversion (DMS SC) workflow for a fully managed experience or 2) download the AWS Schema Conversion Tool (AWS SCT) software to their local drive.
Both options will automatically assess and convert the source database schema and a majority of the database code objects, including views, stored procedures, and functions, to a format compatible with the target database. Any objects that cannot be automatically converted are clearly marked as action items with prescriptive instructions on how to convert, so that they can be manually converted to complete the migration.
AWS SCT can also scan your application source codes for embedded SQL statements and convert them as part of a database-schema-conversion project. During this process, AWS SCT performs cloud-native code optimization by converting legacy Oracle and SQL Server functions to their equivalent AWS service, helping to modernize the applications at the same time of database migration. Once schema conversion is complete, it can help migrate data from a range of data warehouses to Amazon Redshift using built-in data migration agents.
Key benefits of database schema conversion
Key benefits of leveraging DMS Schema Conversion and AWS SCT are:
- Simplify database migrations by automating schema analysis, recommendations, and conversion at scale.
- Compatible with popular databases and analytics services as source and target engines, including Oracle, SQL Server, PostgreSQL, and MySQL.
- Save weeks or months of manual time and resources.
Supported source and target databases for AWS SCT and DMS Schema Conversion
| Target Database | ||
|---|---|---|
| Source Database | AWS Schema Conversion Tool | AWS DMS Schema Conversion |
| Oracle Database |
Aurora MySQL, Aurora PostgreSQL, MariaDB, MySQL, PostgreSQL | Aurora MySQL, Aurora PostgreSQL, MySQL, PostgreSQL |
| Oracle Data Warehouse | Amazon Redshift | Amazon Redshift |
| Microsoft Azure SQL Database | Aurora MySQL, Aurora PostgreSQL, MySQL, PostgreSQL | |
| Microsoft SQL Server | Amazon Redshift, Aurora MySQL, Aurora PostgreSQL, Babelfish for Aurora PostgreSQL (assessment only), MariaDB, Microsoft SQL Server, MySQL, PostgreSQL | Aurora MySQL, Aurora PostgreSQL, MySQL, PostgreSQL |
| Teradata | Amazon Redshift | |
| IBM Netezza | Amazon Redshift | |
| Greenplum | Amazon Redshift | |
| HPE Vertica | Amazon Redshift | |
| MySQL | Aurora PostgreSQL, MySQL, PostgreSQL | Aurora PostgreSQL, PostgreSQL |
| PostgreSQL | Aurora MySQL, Aurora PostgreSQL, MySQL, PostgreSQL | Aurora MySQL, MySQL |
| IBM DB2 LUW | Aurora MySQL, Aurora PostgreSQL, MariaDB, MySQL, PostgreSQL | |
| IBM Db2 for z/OS | Aurora MySQL, Aurora PostgreSQL, MySQL, PostgreSQL | |
| Apache Cassandra | Amazon DynamoDB | |
| SAP ASE | Aurora MySQL, Aurora PostgreSQL, MariaDB, MySQL, PostgreSQL | |
| Amazon Redshift | Amazon Redshift | |
| Azure Synapse Analytics | Amazon Redshift | |
| Snowflake | Amazon Redshift | |
| BigQuery | Amazon Redshift |
More information on DMS Schema Conversion supported database conversions are listed here, whereas AWS SCT conversions are listed here.
Getting started with Schema Conversion
Try DMS Schema Conversion for free today! Check out our Get Started with AWS DMS Schema Conversion video or read our User Guide.
Looking AWS SCT instead? You can download AWS Schema Conversion Tool for your infrastructure of choice from the links below:
