Migrating from Oracle DB to PostgreSQL isn't just a database swap — your Java app needs updated dependencies, configuration changes, and verified behavior. In this episode, watch how the GitHub Copilot app modernization extension handles a database migration end to end, from setting up the app and fixing bugs on the fly to executing the migration task in IntelliJ.

In this episode, you'll learn:
→ How to migrate a Java application's database from Oracle DB to PostgreSQL using GitHub Copilot
→ How to use the app modernization extension in IntelliJ (installed via plugins or the ACPI registry)
→ How Copilot in agent mode analyzes your project, identifies dependencies, and sets up the environment
→ How the tool catches and fixes bugs during setup — like date format issues and README corrections
→ How to use the built-in database migration task to update dependencies, configurations, and function calls
→ How to manually verify app behavior before and after migration

📺 This is Episode 4 of the Modernize Java Apps with AI series — a 9-part, hands-on guide to upgrading legacy Java applications using GitHub Copilot.

🔗 Series playlist: https://www.youtube.com/playlist?list=PLlrxD0HtieHhaBJWlcxGd-kTDikSD4xyD
🔗 GitHub Copilot Modernization extension: https://aka.ms/GHCPMod-Java
🔗 Sample repo: https://github.com/Azure-Samples/java-migration-copilot-samples 

👤 Presented by Sandra Ahlgrimm, Java & AI Advocate, Microsoft

Java #GitHubCopilot #DatabaseMigration #OracleToPostgreSQL #PostgreSQL #JavaModernization #Azure #CloudMigration #AI #IntelliJ

Microsoft Developer

A walkthrough of using GitHub Copilot in agent mode (with IntelliJ) to migrate a Java Spring Boot application from Oracle DB to PostgreSQL on Azure. The demo covers cloning a sample repo, running the app, identifying and fixing bugs (date format, PowerShell issues), and using a JetBrains plugin for database migration tasks. It shows how AI-assisted tooling can automate dependency updates, readme fixes, and database migration steps.

Modernize Databases for the Cloud