Converting database schemas using DMS Schema Conversion
DMS Schema Conversion is a feature of AWS Database Migration Service (AWS DMS) that converts your source database schemas to a format compatible with your target database on Aurora, Amazon RDS, or Amazon Redshift.
To convert a database, you create a migration project for your source and target databases. If you don't have a target database yet, you can use a virtual target and add a real one before you apply your code. DMS Schema Conversion reads your source metadata, and you can run an assessment to see what converts automatically and what needs manual work. You then convert the schema, review the results, and either apply the converted code to your target database or export it as SQL scripts.
Note
DMS Schema Conversion converts your database schema, not your data. To migrate your data, use the data migration features of AWS DMS.
You can use DMS Schema Conversion in the AWS Management Console, with the AWS CLI and SDKs, or with an AI agent that drives it through the AWS API. For more information about using an AI agent, see Using AI agents with DMS Schema Conversion.
Use the following topics to learn how to use DMS Schema Conversion.
Topics
How DMS Schema Conversion works
DMS Schema Conversion converts your schema with a rules-based engine. The rules produce consistent, repeatable results, so you can rely on them across a large schema without checking every object by hand. When the rules can't fully convert an object, DMS Schema Conversion can use generative AI to convert more of it, so you have less to finish manually.
Note
DMS Schema Conversion is a fully managed, web-based feature that builds on the AWS Schema Conversion Tool (AWS SCT) conversion engine.
DMS Schema Conversion uses three resources to work with your databases:
- Instance profile
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Specifies the network and security settings DMS Schema Conversion uses to connect to your source and target databases and to encrypt your conversion data.
- Data provider
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Stores the connection details for a source or target database, such as its type, server name, and port.
- Migration project
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Brings together a source data provider, a target data provider, and an instance profile, along with the AWS Secrets Manager secrets that hold your database credentials.
The following diagram shows how these resources fit together. Each of your source and target databases is represented by a data provider. The migration project uses both data providers and the instance profile, and it's where DMS Schema Conversion converts your schema.
Key capabilities
- Assess your migration
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DMS Schema Conversion reads your source metadata and creates a conversion assessment report that shows what it can convert automatically and what needs manual work. Use the report to estimate the effort of a migration before you commit to it. For more information, see Creating database migration assessment reports with DMS Schema Conversion.
- Convert your schema
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DMS Schema Conversion converts tables, views, stored procedures, functions, and other objects. You can customize the results with transformation rules, which change object names and data types, and with conversion settings for each conversion path. For objects that the rules can't fully convert, generative AI conversion can convert more of them for you to review. For more information, see Using DMS Schema Conversion.
- Apply or export your converted code
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You can compare the source and converted code, and edit the converted SQL. When you're ready, apply the converted code to your target database, or export it as SQL scripts to an Amazon S3 bucket. If your source database uses features that the target database doesn't have, DMS Schema Conversion adds an extension pack that emulates some of them. For more information, see Saving and applying your converted code in DMS Schema Conversion and Using extension packs in DMS Schema Conversion.
Supported conversion paths
The following table lists the conversion paths that DMS Schema Conversion supports, including which paths support generative AI conversion.
| Source database | Target database | Generative AI conversion |
|---|---|---|
| Oracle | Aurora PostgreSQL or RDS for PostgreSQL | Yes |
| Oracle | Aurora MySQL or RDS for MySQL | No |
| Oracle | Amazon Redshift | No |
| SQL Server | Aurora PostgreSQL or RDS for PostgreSQL | Yes |
| SQL Server | Aurora MySQL or RDS for MySQL | No |
| PostgreSQL | Aurora MySQL or RDS for MySQL | No |
| MySQL | Aurora PostgreSQL or RDS for PostgreSQL | No |
| IBM Db2 for LUW | Aurora PostgreSQL or RDS for PostgreSQL | Yes |
| IBM Db2 for z/OS | Aurora PostgreSQL or RDS for PostgreSQL | Yes |
| IBM Db2 for z/OS | Amazon RDS for Db2 | No |
| SAP ASE | Aurora PostgreSQL or RDS for PostgreSQL | Yes |
For the supported versions of each database, see Sources for DMS Schema Conversion and Targets for DMS Schema Conversion. For more information about generative AI conversion, including how it uses cross-Region inference, see Converting database objects with generative AI.
Supported AWS Regions
The following table lists the AWS Regions where you can create a DMS Schema Conversion migration project, including where generative AI conversion is available.
| Region name | Region | Generative AI conversion |
|---|---|---|
| Africa (Cape Town) | af-south-1 | No |
| Asia Pacific (Hong Kong) | ap-east-1 | No |
| Asia Pacific (Taipei) | ap-east-2 | No |
| Asia Pacific (Tokyo) | ap-northeast-1 | Yes |
| Asia Pacific (Seoul) | ap-northeast-2 | No |
| Asia Pacific (Osaka) | ap-northeast-3 | Yes |
| Asia Pacific (Mumbai) | ap-south-1 | No |
| Asia Pacific (Hyderabad) | ap-south-2 | No |
| Asia Pacific (Singapore) | ap-southeast-1 | No |
| Asia Pacific (Sydney) | ap-southeast-2 | Yes |
| Asia Pacific (Jakarta) | ap-southeast-3 | No |
| Asia Pacific (Melbourne) | ap-southeast-4 | No |
| Asia Pacific (Malaysia) | ap-southeast-5 | No |
| Asia Pacific (New Zealand) | ap-southeast-6 | No |
| Asia Pacific (Thailand) | ap-southeast-7 | No |
| Canada (Central) | ca-central-1 | Yes |
| Canada West (Calgary) | ca-west-1 | No |
| Europe (Frankfurt) | eu-central-1 | Yes |
| Europe (Zurich) | eu-central-2 | Yes |
| Europe (Stockholm) | eu-north-1 | Yes |
| Europe (Milan) | eu-south-1 | Yes |
| Europe (Spain) | eu-south-2 | Yes |
| Europe (Ireland) | eu-west-1 | Yes |
| Europe (London) | eu-west-2 | Yes |
| Europe (Paris) | eu-west-3 | Yes |
| Israel (Tel Aviv) | il-central-1 | No |
| Middle East (UAE) | me-central-1 | No |
| Middle East (Bahrain) | me-south-1 | No |
| Mexico (Central) | mx-central-1 | No |
| South America (São Paulo) | sa-east-1 | No |
| US East (N. Virginia) | us-east-1 | Yes |
| US East (Ohio) | us-east-2 | Yes |
| US West (N. California) | us-west-1 | No |
| US West (Oregon) | us-west-2 | Yes |
To convert a database that runs in a Region that isn't listed, create your migration project in a supported Region. Then set up cross-Region connectivity between the VPC in that Region and the VPC where your database runs. For more information, see Setting up a network for DMS Schema Conversion.
