Vish's Journey in Computer Science

The tasks assigned related to Version Management in particular using Git and GitHub were very valuable to my professional journey as an aspiring Software Engineer. However, what surprised me was that a majority of the version management articles were written about managing code written in Application Programming languages such as Java, Python, NodeJS (Java Script) e.t.c.. In this blog I would like to focus on an area in Version Management that is often ignored. I have picked up an interesting Podcast which focusses on Version Control for Databases. Not many people realize the power of Database programming such as Stored Procedures, Functions, Packages, Triggers apart from DDL scripts for objects such as Tables, Views, Materialized Views e.t.c..

In the Postgres.fm podcast episode (https://postgres.fm/episodes/version-control-for-databases) “Version Control for Databases,” hosts Nikolay and Michael explore one of the trickiest challenges in software development—keeping a database’s structure under proper version control. Unlike source code, which fits neatly into systems like Git, databases hold both data and schema that constantly evolve. This discussion opened my eyes to how developers balance reliability with the need to iterate quickly in production environments.

The episode begins by comparing database versioning to traditional software versioning. The hosts note that while code can be reverted with a single Git command, databases contain stateful information that can’t simply be rolled back without consequences. They talk about migrations, tools such as Flyway and Liquibase, and why automated migrations are safer than manual SQL edits. The key takeaway is that treating schema changes as first-class citizens in the development process ensures consistency across environments—from a developer’s laptop to staging and production.

One point that really resonated with me was when the hosts mentioned the risk of “drift”—the gradual divergence between what’s defined in version control and what actually exists in production. I’ve seen this happen in group projects when one teammate updates a table locally but forgets to share the migration script. The podcast offered practical strategies to avoid that: make migrations mandatory, run them through CI pipelines, and ensure rollback scripts are tested just like forward ones.

From a personal standpoint, this episode changed how I think about teamwork and database safety. I learned that version control is not just about tracking lines of code—it’s about ensuring that every system component, including data models, can be reproduced and audited. Going forward, I plan to incorporate database migrations into my Git workflow, even for small personal projects.

To conclude, I would like to thank you for patiently reading my blogpost and encouraging me in my journey to be a good Data Engineer.

URL for Podcast : https://postgres.fm/episodes/version-control-for-databases