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. The service orchestrates the entire migration journey from schema conversion, data migration 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) - us-east-1
Cross-Region Usage: For databases in unsupported regions, you can clone the database to a supported region for transformation, then deploy the results back to your target region.
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
Data migration: Migrates data with integrity validation using AWS Database Migration Service (DMS)
Database objects: Supports triggers, functions, views, computed columns, and identity columns
Validation: Automated data integrity verification and referential integrity checks
Application transformation
Entity Framework transformation: Updates Entity Framework 6.3-6.5 and EF Core 1.0-8.0 configurations for PostgreSQL
ADO.NET transformation: Converts ADO.NET data access code from SQL Server to PostgreSQL providers.
Note
This is a preview feature, available only in the US East (N. Virginia) Region.
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
Wave-based modernization: Organizes large estates into logical migration phases
Dependency mapping: Identifies relationships between applications and databases
Human-in-the-loop (HITL) checkpoints: Provides review and approval gates at critical stages
Automated validation: Tests schema compatibility, data integrity, and application functionality
CI/CD integration: Integrates with existing development pipelines
Deployment
Amazon ECS and Amazon EC2 deployment: Automated containerized deployment with auto-scaling support
Infrastructure-as-code generation: Creates CloudFormation or AWS CDK templates
Automated deployment validation: Verifies successful deployment with health checks
Rollback capabilities: Supports rollback procedures if issues arise
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 |
Note
All SQL Server editions are supported (Express, Standard, Enterprise). SQL Server must be hosted on AWS (RDS SQL Server or SQL Server on EC2) in the same region as AWS Transform.
.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 8.0 |
| ADO.NET | All versions (GA) |
Source code repositories
AWS Transform supports the following repository platforms via AWS CodeConnections:
GitHub and GitHub Enterprise
GitLab.com and GitLab self-managed
Bitbucket Cloud
Azure Repositories
AWS CodeCommit
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
SQL Server hosted on AWS (RDS SQL Server or SQL Server on EC2)
Database and AWS Transform in the same AWS region
Network connectivity between AWS Transform and SQL Server
Database user with VIEW DEFINITION and VIEW DATABASE STATE permissions
Database passwords using printable ASCII characters only (excluding '/', '@', '"', and spaces)
VPC containing the source SQL Server must have subnets in at least 2 different Availability Zones (required for DMS replication subnet groups)
Application requirements
.NET Core 6, 7, or 8 applications
Entity Framework 6.3-6.5 or Entity Framework Core 1.0-8.0, 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
Required service roles created (see setup instructions below)
VPC with appropriate network configuration
Data processing and storage
Processing location
Schema processing occurs in a DMS instance within your VPC
Data migration is optional and can be excluded if required
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
DMS output artifacts
Important
Important for Data Residency: Even when data migration is opted out, 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 1.0-8.0 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 for wave-based migrations.
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: Amazon ECS and Amazon EC2 deployments are 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.
