Migrating Oracle databases to PostgreSQL or MySQL with AWS Schema Conversion Tool (AWS SCT) can present a range of challenges, from unsupported data types to limitations in automated code conversion and potential performance issues. AWS SCT offers powerful capabilities to automate these migrations, but it may not always deliver optimal results or handle complex Oracle constructs efficiently. In these cases, manual adjustments and optimizations are required to ensure a seamless transition to the target database.
At ABCloudz, our team has extensive experience handling these challenges. Through hands-on experience, we’ve developed practical solutions, tips, and tricks for overcoming common AWS SCT limitations and ensuring high performance and accuracy in database migrations. This post serves as a comprehensive catalog of our blog articles, each addressing a specific issue and providing actionable insights to help you successfully migrate your Oracle databases to AWS-based databases like PostgreSQL and MySQL.
Error handling and unsupported SQL clauses
Oracle to PostgreSQL migration with AWS SCT: How to handle unsupported data types
This post explores how to resolve issues that arise when AWS SCT fails to convert Oracle subtypes to PostgreSQL. It covers common challenges like the “Issue 5028 — Unable to convert definition of object with unsupported datatype” error and provides practical solutions, including using direct data type declarations and leveraging %TYPE for local variables.
Oracle to PostgreSQL migration with AWS SCT: How to convert INSERT ALL statement
This post delves into the complexities of converting Oracle’s INSERT ALL statements to PostgreSQL using AWS SCT. It explains why AWS SCT generates a critical Transformer error during this conversion and offers solutions such as replacing INSERT ALL with individual INSERT statements or using UNION ALL for batch inserts. The article also discusses scenarios involving conditional inserts and provides code examples to automate the process, making it essential for maintaining data integrity during Oracle to PostgreSQL migrations.
Oracle to MySQL migration with AWS SCT: How to convert variables of SYS_REFCURSOR datatype
This post examines the challenges of converting Oracle’s SYS_REFCURSOR datatype to MySQL using AWS SCT. It explains why MySQL does not support weakly typed cursors and suggests using strongly typed cursors with static SQL instead. With step-by-step code examples, the article demonstrates how to replace dynamic SQL in Oracle with a static SQL equivalent in MySQL, ensuring efficient handling of cursor-based logic during migrations.
Data type conversions
Handling null and empty string differences in Oracle and PostgreSQL
This post addresses a key issue when migrating from Oracle to PostgreSQL: the difference in how null and empty string values are treated. Oracle treats both as the same, while PostgreSQL distinguishes between them. This article demonstrates these differences with practical examples and provides best practices for handling null values in concatenation, NOT NULL constraints, and complex data types, making it essential for maintaining logic consistency during migration.
Oracle to MySQL migration with AWS SCT: How to handle unsupported NumToYmInterval function
This post discusses the issue of converting Oracle’s NumToYmInterval function to MySQL using AWS SCT. It explains why MySQL does not support storing interval values in variables and provides a workaround using MySQL’s interval literal syntax. The article offers a detailed step-by-step guide to replace NumToYmInterval calls with interval literals in SQL code, ensuring compatibility and smooth conversion during Oracle to MySQL migrations.
Oracle to PostgreSQL migration with AWS SCT: How to handle unsupported NumToDSInterval function
This post explores the complexities of converting Oracle’s NumToDSInterval function to PostgreSQL using AWS SCT. It provides detailed code examples illustrating how to handle these conversions effectively, such as using interval casting or rewriting with date arithmetic expressions.
Performance optimization
How to Optimize Oracle-to-PostgreSQL Migrations Using AWS SCT Extension Pack
This post explores how the AWS SCT Extension Pack helps streamline Oracle-to-PostgreSQL migrations by emulating Oracle-specific functions within PostgreSQL. It discusses the potential performance pitfalls of using emulated functions and offers best practices for replacing them with native PostgreSQL functions.
Oracle to MySQL migration with AWS SCT: How to convert BULK COLLECT clause
This post tackles the issue of converting Oracle’s BULK COLLECT clause to MySQL using AWS SCT. It explains why MySQL does not support bulk collect operations and how to replace them with standard SELECT statements inside a loop for row-by-row processing. The article provides a comprehensive example illustrating how to manually adjust Oracle code to maintain performance and avoid conversion errors during large data migrations.
Architectural considerations
Handling PostgreSQL Routines with More Than 100 Arguments
This post addresses the common issue of migrating complex Oracle procedures to PostgreSQL when they contain more than 100 arguments. PostgreSQL imposes a limit of 100 arguments per routine, which can pose challenges during migration. The article introduces an effective solution using composite data types to bypass this restriction, consolidating arguments into a single structured object.
Conclusion
If you’re considering migrating a database from Oracle to PostgreSQL or MySQL using AWS SCT, or are currently working on one, we suggest reviewing each of these posts to better understand the challenges and solutions involved in using AWS SCT. Save this page for easy access to practical advice and best practices. For additional support with your database migration, feel free to get in touch. Our team has extensive experience managing migrations and can help ensure your transition is smooth and successful.
