SQL Server modernization
AWS Transform for SQL Server Modernization is an AI-powered service that automates the full-stack modernization of Microsoft SQL Server databases and their associated .NET applications to Amazon Aurora PostgreSQL. AWS Transform converts SQL Server storage objects and code objects (stored procedures) using an agentic, interactive experience. The service orchestrates the migration journey from schema conversion, synthetic data generation, and modifying application code to match the new target PostgreSQL, making your teams more productive by automating complex and labor-intensive tasks.
Supported regions
AWS Transform for SQL Server is available in US East (N. Virginia), Europe (Frankfurt), Europe (London), Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Tokyo), Asia Pacific (Sydney), and Canada (Montreal).
Cross-Region Usage: For databases in unsupported regions, AWS Transform for full-stack Windows modernization supports cross-region deployment of converted Amazon Aurora PostgreSQL databases. You can upload SQL Server Database Design Language (DDL) files and set a target AWS Region in the transformation plan to convert the database and deploy the resulting Aurora PostgreSQL cluster to a different AWS Region. If you have data residency, latency, or disaster recovery requirements, you can start a job in any of the available AWS Regions and deploy the target cluster in the destination Region of your choice.
Capabilities and key features
Database transformation
Schema conversion: Automatically converts SQL Server schemas to Aurora PostgreSQL, including tables, views, indexes, constraints, and relationships
Stored procedure transformation: Converts T-SQL stored procedures to PL/pgSQL with AI-enhanced accuracy
Database objects: Supports triggers, functions, views, computed columns, and identity columns
Synthetic data generation: Generate synthetic data for the converted PostgreSQL database to validate functionality
Validation: Automated functional equivalence checks for transformed database objects, stored procedures, and functions
Application transformation
Entity Framework transformation: Updates Entity Framework 6.3-6.5 and EF Core 1.0-10.0 configurations for PostgreSQL
ADO.NET transformation: Converts ADO.NET data access code from SQL Server to PostgreSQL providers.
Connection string updates: Automatically updates all database connection strings to the new target PostgreSQL database
Database provider changes: Replaces SQL Server providers with Npgsql (PostgreSQL provider)
ORM configuration updates: Modifies data type mappings, identity columns, and database-specific configurations
Orchestration & validation
Dependency mapping: Identifies cross-database references and relationships between applications and databases to create a modernization plan
Human-in-the-loop (HITL) checkpoints: Provides review and approval gates at critical stages
Automated validation: Tests schema compatibility, data integrity, and application functionality
Functional equivalence validation: Loads the target database into a container to validate functional equivalence between the source and converted database
Deployment
Aurora PostgreSQL cluster: Deploy the converted PostgreSQL database to an Amazon Aurora cluster
Deployment capabilities: Deploy to an existing cluster, or let AWS Transform automatically create a new cluster
Supported versions and project types
SQL Server versions
AWS Transform supports the following SQL Server versions:
| SQL Server Version | Support Status |
|---|---|
| SQL Server 2022 | Supported |
| SQL Server 2019 | Supported |
| SQL Server 2017 | Supported |
| SQL Server 2016 | Supported |
| SQL Server 2014 | Supported |
| SQL Server 2012 | Supported |
| SQL Server 2008 R2 | Supported |
.NET versions
| .NET Version | Support Status |
|---|---|
| .NET 10 | Supported |
| .NET 8 | Supported |
| .NET 7 | Supported |
| .NET 6 (Core) | Supported |
| .NET Framework 4.x and earlier | Not Supported |
Important
Legacy .NET Framework 4.x and earlier versions are not supported. If your application uses .NET Framework, you must first upgrade to .NET Core 6+ using AWS Transform for .NET modernization before using SQL Server transformation capabilities.
Entity Framework versions
| Framework | Supported Versions |
|---|---|
| Entity Framework 6 | 6.3, 6.4, 6.5 |
| Entity Framework Core | 1.0 through 10.0 |
| ADO.NET | All versions (GA) |
Source code repositories
AWS Transform supports the following source code platforms:
GitHub and GitHub Enterprise Server
Bitbucket Cloud and Bitbucket Data Center
Azure DevOps and Azure DevOps Server
Amazon S3
Direct upload of source code zip files
Target database
AWS Transform targets Amazon Aurora PostgreSQL (PostgreSQL 15+ compatible) with support for the latest Aurora features and optimizations.
Technical requirements
Database requirements
Microsoft SQL Server version 2008 R2 through 2022
Database user with VIEW DEFINITION and VIEW DATABASE STATE permissions
Database passwords using printable ASCII characters only (excluding '/', '@', '"', and spaces)
Application requirements
.NET 6, 7, 8, or 10 applications
Entity Framework 6.3-6.5 or Entity Framework Core 1.0-10.0, or ADO.NET
Database connections discoverable in source code
Applications successfully build and run
Source code in supported repository platforms
AWS account requirements
AWS account with administrator access
IAM Identity Center enabled
Data processing and storage
Processing location
Transformation artifacts are stored in the AWS Transform service region
Stored artifacts
The following items are stored in the service region:
Agent logs
Assessment results
SQL schema files
Important
Important for Data Residency: Metadata and processing artifacts are stored in the service region. This is important for organizations with strict data residency requirements.
Artifact management
Customer option for encryption using your own KMS keys
Defined TTL (time-to-live) period for all artifacts
Artifacts can be downloaded for offline storage
Application requirements
Legacy .NET Framework
Limitation: .NET Framework 4.x and earlier versions are not supported.
Workaround: Use AWS Transform for .NET to upgrade to .NET Core 6+ first, then use SQL Server transformation.
Entity Framework versions
Limitation: Only Entity Framework 6.3-6.5 and EF Core 1.0-10.0 are supported.
Workaround: Upgrade to a supported Entity Framework version before transformation.
VB.NET applications
Limitation: VB.NET is not supported.
Workaround: Convert to C# or use AWS Transform custom to convert from VB.NET to C#.
Cross-database dependencies
Limitation: Challenges when database schemas interact across multiple databases.
Workaround: Review and refactor cross-database queries before migration. Consider consolidating databases or using PostgreSQL schemas.
Impact: May require human intervention for complex cross-database scenarios.
Repository-database coupling
Limitation: Challenges when a single repository serves multiple databases.
Workaround: Consider repository restructuring or phased migration approach.
Impact: May require additional planning when a repository spans multiple databases.
Infrastructure requirements
Single account/region per job
Limitation: Each transformation job targets one AWS account and region.
Workaround: Create multiple transformation jobs for multi-account or multi-region deployments.
Deployment targets
Limitation: AWS Transform supports deploying to Amazon Aurora as the target only. Amazon RDS cluster creation is not supported.
Repository requirements
Private NuGet packages
Limitation: Private NuGet packages require additional configuration.
Workaround: Configure private NuGet feeds in transformation settings before starting the job.
