Building a Bubble.io App? Here’s How to Scale It Properly

Hey,

Building an app with Bubble.io is easy, but scaling it to handle more users, data, and features is where things get tricky. Many no-code developers make the mistake of launching an app that works fine at first but breaks down once traffic increases.

This week, I’m sharing the best strategies to make your Bubble.io app scalable, so it stays fast, secure, and maintainable as your user base grows.

1. Plan Your Database for Scalability

Your database structure directly affects performance. A poorly designed database can slow down searches, increase page load times, and create unnecessary complexity.

How to Optimise:
✅ Use Option Sets for static data (e.g., user roles, categories) instead of storing them in the database.
✅ Store repetitive data as references instead of duplicating it. Example: Instead of saving a user’s name multiple times in different places, store their User ID and reference it dynamically.
✅ Use separate data types for frequently accessed vs. rarely used data. Example: Instead of having a single "User" data type with 30 fields, separate profile info into a different data type to reduce load time.

Pro Tip: Run test searches in Bubble’s Debugger to see how long your database queries take. If it’s slow, rethink your structure.

2. Use Backend Workflows to Reduce Load

When scaling, frontend workflows can slow down your app if too many actions happen on-page. Instead, shift heavy processing to backend workflows.

How to Do It:
✅ Use scheduled workflows for tasks that don’t need instant execution (e.g., sending emails, generating reports).
✅ Offload complex calculations to the backend rather than processing them in a repeating group.
✅ Use recursive workflows for handling large datasets instead of running everything at once.

Example: Instead of deleting 500 outdated entries in a single workflow, schedule a recursive workflow to process 50 at a time.

3. Reduce Repeating Group Load Time

Repeating Groups are one of the most resource-intensive elements in Bubble. If your app loads a large dataset every time a page opens, it can slow everything down.

How to Fix It:
✅ Use Pagination or Infinite Scroll – Load only a limited number of records at a time.
✅ Limit the number of columns displayed – Fetch only essential data and load extra details when needed.
✅ Use Pre-Filtered Searches – Instead of filtering on-page, apply constraints in your database search for faster results.

Pro Tip: For large lists, consider using an external database (e.g., Xano or Airtable) for better performance.

4. Optimise API Calls for Speed and Cost

APIs can slow your app if not used efficiently. If you rely on external services (like OpenAI, Stripe, or Zapier), optimising API calls can save you both time and money.

How to Do It:
✅ Cache responses – If an API returns the same data frequently, store it in the database instead of making multiple calls.
✅ Use Webhooks – Instead of polling APIs repeatedly, set up webhooks to trigger updates when new data is available.
✅ Batch Requests – Instead of calling an API multiple times, use bulk processing if supported.

Example: Instead of calling an API for every user action, schedule a batch API call in the backend.

5. Monitor App Performance and Fix Bottlenecks

Scaling requires ongoing monitoring to catch performance issues before they become a problem.

How to Do It:
✅ Use Bubble’s Server Logs to check which workflows take the longest to execute.
✅ Enable Capacity Monitoring to see if your app is hitting Bubble’s server limits.
✅ Track page load speed and workflow execution time with Google Lighthouse or Bubble’s built-in performance tools.

Pro Tip: If your app is slow during peak usage, consider upgrading your Bubble plan or using dedicated hosting.

That’s a Wrap!

If you’re serious about scaling your Bubble.io app, these strategies will help you avoid performance issues and ensure long-term success.

What’s been your biggest challenge with scalability so far? Hit reply and let me know—I’d love to help!

Until next week,
Stackless