I’ve been working on a virtual scrolling engine that intentionally breaks from how most existing solutions approach the problem.
Rather than anchoring scroll position to global pixel space or cumulative height math, this introduces a state-based scrolling model that keeps scrolling fast and precise regardless of dataset size.
In practice, this allows smooth, pixel-perfect scrolling through millions of variable-height rows while keeping DOM size constant and per-frame work bounded.
No GPU transforms.
No full height maps.
No precomputation or estimation passes.
The interesting part isn’t what framework it uses (it’s framework-agnostic), but that it challenges an assumption most virtual scrollers share: that scroll position must be derived from absolute pixel space.
I’m not claiming this replaces every existing approach, but if adopted more broadly, I think this model could meaningfully change how large, variable-height datasets are virtualized on the web.
👉
Demos -
