Using deck.gl in Bubble to Visualize Large Geospatial Datasets (Heatmaps, Scatterplots, 3D Columns, Text Layers)

When building map-based features in Bubble, showing basic markers or shapes is usually straightforward. However, things can get tricky when you need to work with large geospatial datasets or create more data-driven visualizations.

Some common challenges I’ve noticed include:

  • Performance issues when rendering thousands of points

  • Difficulty showing density or intensity instead of individual markers

  • Limited ways to compare values across locations

  • Missing support for advanced or 3D map visualizations

  • Not enough flexibility for labels and contextual text on maps

In analytics-heavy apps—such as dashboards, logistics platforms, mobility apps, or location-based SaaS products—markers alone often don’t communicate enough information.

To help solve this issue, I’ve been working on a Bubble plugin that integrates deck.gl layers, making it possible to add advanced map visualizations such as:

  1. Column layers to represent values as 3D bars
  2. Scatterplot layers for large datasets of points with styling control
  3. Heatmap layers to visualize density and intensity
  4. Text layers to show labels, annotations, or values directly on the map

The idea is to extend Bubble’s existing mapping capabilities and make it easier to build high-performance, scalable map visualizations without leaving the Bubble ecosystem.

I’d really like to hear from the community:

  • What map limitations have you encountered in Bubble?

  • Are you working with dense or large location-based datasets?

  • Do features like heatmaps, 3D columns, or text labels on maps fit your use cases?

Looking forward to your feedback and discussion.

Checkout the plugin here

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