Data Migration with AWS Schema Conversion tool (SCT)

Introduction

Database migration is crucial for organizations looking to transition to the cloud. AWS offers a powerful tool called AWS Schema Conversion Tool (SCT) to simplify converting database schemas and code objects from various source databases to formats compatible with target databases. In this tech blog, we will explore how AWS SCT can help you assess the complexity of your migration, automatically convert database schemas, and manage migration projects.

Converting Database Schemas with AWS SCT

• Assess and Convert: The AWS Schema Conversion Tool, part of the AWS Database Migration Service (AWS DMS), is designed to make database migrations predictable. It automatically converts source database schemas and most database code objects, including tables, views, stored procedures, functions, data types, and synonyms, into a format compatible with the target database. It significantly reduces the manual effort required for migration.
• Manual Conversion: In cases where automatic conversion is not feasible, AWS SCT marks objects that need manual conversion. Users can then manually convert these objects to ensure a successful migration.

Key Components of AWS SCT

• Instance Profiles: Instance profiles specify network and security settings required for the migration process.
• Data Providers: Data providers store database connection credentials, enabling SCT to establish connections with source and target databases.
• Migration Projects: Migration projects are containers that encompass data providers, instance profiles, and migration rules. These projects serve as the core framework for database migrations using AWS SCT.

Supported Source and Target Databases

AWS SCT supports various source and target databases, making it a versatile tool for various migration scenarios.

• Source Databases: AWS SCT can connect to a variety of source databases. This includes both commercial databases and open-source databases. Examples of supported source databases include Oracle, Microsoft SQL Server, MySQL, PostgreSQL, and more.
• Target Databases: AWS SCT supports a broad range of target databases. The target database is the system to which you want to migrate your data. AWS provides managed database services for various engines, and SCT can help you convert your schema to work with these services. This may include Amazon RDS (Relational Database Service) instances using different database engines, such as Amazon Aurora, PostgreSQL, MySQL, and Microsoft SQL Server.

Understanding the Schema Conversion Process

The schema conversion process with AWS SCT involves the following:

• Network Setup: Users can set up network configurations to establish secure connections between source and target databases.
• Data Provider Configuration: AWS SCT enables users to configure source and target data providers, facilitating database connections.
• Migration Project Management: Migration projects are created and managed within AWS SCT, bringing together data providers, instance profiles, and migration rules.
• Assessment Reports: AWS SCT allows you to generate database migration assessment reports, summarizing schema conversion tasks and highlighting objects that require manual intervention.
• Conversion: After configuring source and target data providers, AWS SCT automates the conversion of source database schemas into the target database format. Users can review and save the converted code for reference.
• Transformation Rules: Transformation rules can be set up to modify data types, move objects between schemas, or change object names, offering flexibility during the migration process.
• Extension Packs: For cases where certain source database features cannot be converted directly, AWS SCT creates extension packs in the target database to emulate these features, ensuring compatibility.
• Applying Converted Code: Finally, users can apply the converted code and extension pack schema to the target database, completing the migration process.

Conclusion

However, it’s essential to understand its limitations and use it with other tools and best practices to ensure a seamless migration experience.

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