Why You Should Avoid Loading Data on Demand with OrgChart JS

When working with OrgChart JS, one of the tempting strategies is to load data on demand — meaning you only fetch and display parts of the chart as the user expands nodes. At first glance, this seems efficient: less data upfront, faster initial rendering, and the ability to scale to large datasets. But in practice, it often creates more problems than it solves.

Let’s go through why you should avoid loading OrgChart JS data on demand, and what you should do instead.

1. Loss of Built-in Features

OrgChart JS is designed with a lot of powerful features:

• Search across all nodes

• Export to PDF, PNG, SVG

• Layout and auto-balance of the hierarchy

• Drag-and-drop editing

All of these rely on having the full dataset in memory. If you only load a fraction of the data, these features either break or behave inconsistently.

2. Performance Is Already Optimized

One of the main reasons people consider on-demand loading is performance. But OrgChart JS is already optimized to handle thousands of nodes efficiently:

• Virtual scrolling ensures smooth navigation.

• Rendering is smart, only painting what’s visible.

• Data structures are memory-friendly compared to DOM-heavy approaches.

In other words: the chart doesn’t actually render all nodes at once. You can safely load your entire dataset upfront without worrying about performance issues in most real-world use cases.

3. Complexity Without Real Benefit

Implementing on-demand loading means:

• Writing extra backend APIs to fetch child nodes.

• Managing “loading” indicators in the chart.

• Dealing with edge cases (e.g., what happens if a parent is expanded twice, or if relationships span multiple branches).

This adds a lot of development overhead with almost no user benefit, since OrgChart JS already solves performance concerns internally.

4. Better Alternatives Exist

If your chart data is truly massive (tens of thousands of nodes), you still don’t need on-demand loading. Instead for example you can:

• Pre-filter by department or region and let the user switch datasets.

• Allow progressive disclosure at the UI level (e.g., showing summaries, then expanding into details), but keep the data loaded internally.

This way, you preserve all features, keep the user experience smooth, and avoid technical headaches.

Conclusion

Loading data on demand in OrgChart JS might seem attractive, but it usually backfires: broken features, fragmented user experience, and unnecessary complexity.

Instead, load all data upfront and let OrgChart JS do what it was built to do: efficiently handle large org charts with full functionality intact.

Your users will thank you for a chart that works seamlessly — no missing pieces, no waiting for nodes to load, just the complete organizational picture at their fingertips.