AWS Schema Conversion Tool (SCT): A Comprehensive Guide

AWS Schema Conversion Tool (SCT): A Comprehensive Guide

12/13/20243 min read

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photo of white staircase

AWS Schema Conversion Tool (SCT): A Comprehensive Guide

Table of Contents

  1. Introduction

  2. What is AWS Schema Conversion Tool (SCT)?

  3. Features of AWS SCT

  4. Use Cases of AWS SCT

  5. How AWS SCT Works

  6. Supported Databases

  7. Setting Up AWS SCT

  8. Schema Conversion Process

  9. AWS SCT User Interface Overview

  10. Converting Schemas with AWS SCT

  11. Data Type Mapping and Conversion

  12. Object Conversion

  13. Customization and Rule Creation

  14. Assessment Reports

  15. Generating and Reviewing Reports

  16. Code Conversion and Optimization

  17. Best Practices for AWS SCT

  18. Common Challenges and Troubleshooting

  19. Use Cases and Real-World Examples

  20. Frequently Asked Questions (FAQ)

  21. Conclusion

1. Introduction

The AWS Schema Conversion Tool (SCT) is a powerful tool that simplifies the process of migrating database schemas from one database engine to another. It helps businesses migrate on-premises or cloud-based databases to AWS cloud-native databases like Amazon RDS, Amazon Aurora, or Amazon Redshift.

2. What is AWS Schema Conversion Tool (SCT)?

AWS SCT is a client-side tool that automates the conversion of database schemas from commercial database engines (like Oracle, SQL Server, and DB2) to open-source or AWS cloud-native databases (like Amazon Aurora, MySQL, PostgreSQL, and Amazon Redshift). The tool identifies schema objects that require manual intervention and provides guidance on how to resolve them.

3. Features of AWS SCT

  • Schema Conversion: Converts the entire schema, including tables, indexes, views, stored procedures, functions, and triggers.

  • Cross-Database Compatibility: Supports migration between multiple database engines.

  • Assessment Reports: Provides a detailed assessment report on the level of effort required for migration.

  • Customization Rules: Allows the creation of custom rules to modify the conversion process.

  • Code Conversion: Converts SQL code, including stored procedures, functions, and scripts.

  • User-Friendly Interface: Offers a graphical user interface (GUI) for easy schema analysis and conversion.

4. Use Cases of AWS SCT

  1. Database Migration: Migrating from on-premises Oracle, SQL Server, or DB2 to Amazon Aurora, RDS, or Redshift.

  2. Modernization Projects: Modernizing legacy applications by moving to cloud-native AWS databases.

  3. Cost Reduction: Reducing licensing costs by switching from commercial databases to open-source alternatives.

  4. Hybrid Cloud Migration: Converting on-premises databases to hybrid cloud or AWS cloud-native architectures.

5. How AWS SCT Works

AWS SCT follows a four-step process for schema conversion:

  1. Source Connection: Connect to the source database (e.g., Oracle, SQL Server).

  2. Schema Analysis: Identify objects to convert and assess the complexity of the conversion.

  3. Schema Conversion: Automatically convert the schema to the target database format.

  4. Export/Apply Changes: Apply the converted schema to the target database.

6. Supported Databases

Source Databases:

  • Oracle

  • Microsoft SQL Server

  • IBM Db2

  • Netezza

  • Teradata

Target Databases:

  • Amazon Aurora (MySQL and PostgreSQL)

  • Amazon RDS (MySQL, PostgreSQL, MariaDB, SQL Server, Oracle)

  • Amazon Redshift

  • Open-source MySQL and PostgreSQL

7. Setting Up AWS SCT

  1. Download and Install: Download AWS SCT from AWS's official site and install it on your local machine.

  2. Configure Source and Target: Define the source and target database connections.

  3. Create Project: Create a new project to store all schema conversion tasks.

8. Schema Conversion Process

  • Step 1: Connect to source and target databases.

  • Step 2: Use the assessment report to identify objects that require manual changes.

  • Step 3: Convert the schema using SCT.

  • Step 4: Export and apply the converted schema to the target database.

9. AWS SCT User Interface Overview

  • Project Explorer: Displays the list of objects in the schema.

  • Action Panel: Displays actionable items like "Convert", "Export", and "Apply".

  • Assessment Report: Shows analysis of schema compatibility.

10. Converting Schemas with AWS SCT

  1. Start Conversion: Click the "Convert" button to initiate the schema conversion.

  2. Review Issues: Review the action items that require manual intervention.

  3. Apply Changes: Apply the converted schema to the target database.

11. Data Type Mapping and Conversion

AWS SCT maps data types from the source database to the target database. For example:

  • Oracle VARCHAR2 -> MySQL VARCHAR

  • SQL Server NVARCHAR -> PostgreSQL TEXT

12. Object Conversion

AWS SCT converts objects such as:

  • Tables

  • Views

  • Indexes

  • Constraints

  • Stored Procedures

  • Functions

13. Customization and Rule Creation

Create custom rules for schema conversion, such as renaming columns or adjusting data types to suit specific business needs.

14. Assessment Reports

The assessment report highlights objects that may require manual intervention and provides recommendations for successful conversion.

15. Generating and Reviewing Reports

  • Generate reports after initial analysis.

  • Review issues related to compatibility and manual changes.

16. Code Conversion and Optimization

AWS SCT automatically converts procedural code (like PL/SQL) into SQL code that is compatible with the target database.

17. Best Practices for AWS SCT

  1. Review Assessment Reports: Address any manual changes.

  2. Use Custom Rules: Create rules to streamline the process.

  3. Test Before Deployment: Validate converted schemas in a test environment.

18. Common Challenges and Troubleshooting

  • Data Type Mismatches: Use customization rules to resolve data type conflicts.

  • Procedure Conversion: Some stored procedures may require manual intervention.

19. Use Cases and Real-World Examples

Example 1: Migrating from Oracle to PostgreSQL

  • Source: Oracle 11g

  • Target: Amazon RDS PostgreSQL

  • Process: Use AWS SCT to convert the schema and apply it to PostgreSQL.

Example 2: Migrating SQL Server to Redshift

  • Source: Microsoft SQL Server 2016

  • Target: Amazon Redshift

  • Process: Use AWS SCT to convert SQL Server schema and data warehouse objects to Redshift.

20. Frequently Asked Questions (FAQ)

Q1: Can AWS SCT convert stored procedures?

  • Yes, AWS SCT converts stored procedures, but manual intervention may be required.

Q2: Is AWS SCT free?

  • Yes, AWS SCT is free to use.

21. Conclusion

AWS Schema Conversion Tool (SCT) is a robust, client-side tool that facilitates seamless database migration from on-premises or legacy environments to AWS. By automating schema conversion, data type mapping, and code conversion, AWS SCT reduces migration time and effort, enabling businesses to modernize their data architecture.