In Oracle-to-PostgreSQL migrations, schema objects like tables and indexes convert readily. Stored procedures, functions, packages, and triggers are where the work becomes time-consuming, resource-intensive, and challenging. These objects contain complex PL/SQL logic that takes senior database architects days or weeks to rewrite manually, creating a bottleneck that delays migrations and increases cost.
AWS Database Migration Service Schema Conversion (AWS DMS SC) handles schema and DML conversion well and includes generative AI–powered conversion capabilities. Complex PL/SQL patterns such as transaction control, exception handling, and Oracle-specific functions still have cases where automated conversion is incomplete. Those remaining objects end up in a manual queue.
In this post, you learn how to build a generative AI–powered migration assistant that helps automate portions of the last mile of code conversion. Using Anthropic’s Claude Sonnet 4.6 on
