Rendering a few hundred rows in React frameworks isn't particularly difficult.
Rendering 100,000+ rows, while supporting editing, filtering, sorting, real-time updates, and smooth scrolling, is a completely different problem.
That's where data-grid architecture starts to matter.
Why Traditional Tables Struggle
A traditional React table can become expensive when a large dataset is rendered directly into the DOM.
The more rows and columns you render, the more work the browser has to perform.
Modern data grids address this using techniques such as virtual scrolling.
Virtual Scrolling
Instead of rendering every row, the grid renders the rows currently visible to the user plus a buffer.
When the user scrolls, the grid can recycle those rows instead of continuously creating and removing DOM elements.
This keeps the amount of rendered content relatively small even when the underlying dataset is very large.
What About Large Numbers of Columns?
Vertical virtualization isn't always enough.
A dataset with hundreds of columns can still create a significant rendering cost.
That's where column virtualization, or horizontal buffering, comes in.
The grid renders only the columns that are currently visible instead of creating DOM elements for every column.
Together, row and column virtualization can make large datasets much more manageable.
Other Enterprise Requirements
Performance isn't the only consideration.
An enterprise data grid should also be evaluated for:
Accessibility
Keyboard navigation
Filtering and sorting
Inline editing
Grouping
Real-time data
Licensing
Release cadence
Backward compatibility
Long-term maintenance
The guide compares several popular approaches, including AG Grid, TanStack Table, MUI X Data Grid, and Ext JS via ReExt.
The interesting part is that they solve the problem in different ways — from standalone grids to headless table logic and broader framework-based solutions.
How are you handling large datasets in your React applications?
Are you relying on virtualization, server-side processing, pagination, or a combination of approaches?
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