Designing PostgreSQL Database Using AI: Why You Should Avoid ENUMs & How MySQL Offers More Storage Options

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In the earlier part of the series we looked at how to install & do bare minimum postgres configuration from best practices and security standpoint. In this part we will look at some of our experiences using AI to define our schema and some comparison points between MySQL and Postgres.

AI-powered tools like ChatGPT, Gemini, and DeepSeek have changed how developers approach database design. Today, teams routinely use AI to generate schemas, validate ideas, and build quick prototypes. But how good are these AI-generated schemas in real-world applications?

As we experimented with AI for designing our PostgreSQL database, we noticed that AI often missed crucial best practices. In this post, we will share some real-world scenarios where AI could have done a better job, and we will also compare PostgreSQL and MySQL in terms of storage optimization and data type flexibility.

When we started using it, we were expecting AI to not only generate the schema quickly but also for ensure by default