High Performance SwiftData Apps

My 3000-word apology for killing my iPhone processor

A few weeks ago, I released a new app to the world. Unfortunately, nobody seemed to like it very much. Let’s chalk it up to a rare Jacob Bartlett miss.

But there is an untold story behind the development of the app. A story with nothing to do with my outdated early 2000’s anime references.

A story of SwiftData gone wrong.

And a story of performance pain, of data integrity, and of a successful migration.

I took my nearly-complete app for a test-drive at London Comic-Con. The app took photos and converted them into Top-Trumps-style trading cards with customised names, relevant stat ratings, and different UI effects based on rarity.

I wanted to collect some cool Comic-Con costumes.

In product terms, the app was a massive success. The cosplayers looked great, the shader effects popped, and my client-hosted AI model was handing out accurate names and stats.

But I had twin problems creeping up…

My full post-comic-con haul. Who needs merch when you have photos?

Every time I saved a new card, the app would get slower.

And slower.

And slower.

My battery dwindled rapidly.

I went into low-power mode.

And slower.

And hotter.

And it started crashing.

And got slower.

You get the idea.

Eventually I was waiting 20 seconds between taking a photo and being able to save the card to my collection. Then it would just crash every time.

Something was very wrong with the way I’d implemented SwiftData.

I got home. I knew I had to fix it.

But I also needed to keep my device safe, otherwise I’d lose my hard-earned Comic-Con collection.

So I had my 2 objectives:

1. Optimise my SwiftData usage to make my app performant…

2. …without losing all the existing cards I’ve collected

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