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 | Schema Conversion Tool (AWS SCT) | AWS DMS Schema Conversion |
| Oracle Database |
Amazon Aurora MySQL-Compatible Edition (Aurora MySQL), Amazon Aurora PostgreSQL-Compatible Edition (Aurora PostgreSQL), MariaDB 10.5, MySQL, PostgreSQL | Aurora MySQL, Aurora PostgreSQL, MySQL, PostgreSQL |
| Oracle Data Warehouse | 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 (only for assessment reports), 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 | |
| PostgreSQL | Aurora MySQL, Aurora PostgreSQL, MySQL, PostgreSQL | |
| 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.
Supported AWS SCT use cases
To summarize, AWS SCT can be used to:
- Copy a database schema from a source to a target
- Convert a database or data warehouse schema
- Analyze a database to determine the conversion complexity
- Analyze a database to determine any possible restrictions to running on Amazon RDS
- Analyze a database to determine if a license downgrade is possible
- Convert embedded SQL code in an application
- Migrate data warehouse data to Amazon Redshift
Download and install AWS SCT on Windows and Linux
You can download AWS Schema Conversion Tool for your infrastructure of choice from the links below:
