Async Virtualization That Actually Feels Instant

WPF DataGrid speed hinges on fetch and render. Use async data virtualization to free the UI thread and row recycling to cut visual churn. In .NET 8 with 1,000,000 rows, we saw smooth fast scroll, ~60 FPS, sub-50 ms input, and bounded memory via windowed paging. Turn on virtualization/recycling, fetch off-UI, keep templates light, and verify with ETW/WPA. Smoothness wins.

WPF DataGrid Performance at Scale

If your WPF DataGrid starts to hitch the moment you hit a few hundred thousand rows, the bottleneck isn’t just “too much data”—it’s how the grid handles it. Async data virtualization and row recycling eliminate UI stalls by keeping the render thread free while data loads in the background.

What causes freezes in WPF grids

Synchronous data fetches on the UI thread
Excessive layout passes during fast scroll
Row template churn without recycling
Binding overhead from heavyweight cell templates

Our test setup

Dataset: 1,000,000 rows, mixed column types, server-side filter capability
Interactions: fast scroll (mouse + scrollbar), multi-column group, filter text entry
Environment: Release build, x64, .NET 8, hardware acceleration enabled

What changed with async virtualization

Data requests happen off the UI thread
Rows recycle; visual tree churn is minimized
Placeholders render immediately; data fills progressively
Input stays responsive even under heavy fetch

Expected performance profile

Scrolling retains visual continuity with stable 60 FPS
Input latency stays under ~50 ms while data loads
Memory usage remains bounded due to page/windowing

Implementation pattern (simplified)

Use an async-friendly collection and page/window manager
Kick off data fetch on background threads
Bind to virtualization-aware views
Enable row recycling and lightweight cell templates

Developer checklist

Turn on row virtualization and recycling
Move data fetches off the UI thread
Use lightweight cell templates and value converters sparingly
Group/filter via async-capable, incremental sources
Measure with ETW/WPA to confirm UI thread headroom

Why it matters

Users feel stutter more than they notice raw milliseconds. Smoothness is the difference between “good enough” and “we’re buying this.”

Try Xceed DataGrid for WPF with async virtualization and see the difference in under an hour. Start your 45-day trial:

https://xceed.com/trial/

FAQ

Does async virtualization work with grouping and filtering?

Yes—use incremental sources so group/filters compute off the UI thread and hydrate progressively.

Will virtualization change my data model?

No; you wrap sources in a virtualization-aware layer.

How do I measure if it’s working?

Profile UI thread time with ETW/WPA; you should see input/render threads with headroom during fast scroll.