Want to skip to the implementation? Check out these React examples:
Install and import the React virtualizer adapter from @tanstack/react-virtual. TanStack Table still owns rows, columns, and table state; the virtualizer owns scroll indexes and measurements. Also see the TanStack Virtual table example.
The TanStack Table packages do not come with any virtualization APIs or features built in. Virtualization is a rendering strategy, not a table feature. You can use TanStack Table with any virtualization library, but the official examples use TanStack Virtual.
TanStack Table and TanStack Virtual solve different parts of the problem:
Use virtualization when your table has a very large number of rows, columns, or both. Virtualization keeps the DOM small by only rendering the items that are visible in the scroll viewport plus a small overscan buffer.
Virtualization is not a replacement for server-side pagination, filtering, or sorting. If the data is virtualized on the client, the data still needs to exist on the client. If your dataset is too large to load into the browser, use server-side data operations or infinite scrolling.
For small tables, normal rendering is simpler and usually preferable.
Install the React virtualizer adapter:
npm install @tanstack/react-virtualnpm install @tanstack/react-virtualThe React examples use useVirtualizer from @tanstack/react-virtual. TanStack Table still owns rows, columns, headers, cells, sizing, sorting, filtering, and other table state; TanStack Virtual decides which item indexes should render for the current scroll position.
The table itself is set up like any other v9 table. Declare your features with tableFeatures() and create the table with useTable; nothing about virtualization changes the table setup.
import {
columnSizingFeature,
rowSortingFeature,
createSortedRowModel,
sortFns,
tableFeatures,
useTable,
} from '@tanstack/react-table'
import { useVirtualizer } from '@tanstack/react-virtual'
const features = tableFeatures({
columnSizingFeature,
rowSortingFeature,
})
const table = useTable({
features,
rowModels: {
sortedRowModel: createSortedRowModel(sortFns),
},
columns,
data,
})import {
columnSizingFeature,
rowSortingFeature,
createSortedRowModel,
sortFns,
tableFeatures,
useTable,
} from '@tanstack/react-table'
import { useVirtualizer } from '@tanstack/react-virtual'
const features = tableFeatures({
columnSizingFeature,
rowSortingFeature,
})
const table = useTable({
features,
rowModels: {
sortedRowModel: createSortedRowModel(sortFns),
},
columns,
data,
})Most virtualized table implementations follow the same pattern:
Here is a compact row virtualization example:
const rows = table.getRowModel().rows
const rowVirtualizer = useVirtualizer({
count: rows.length,
getScrollElement: () => tableContainerRef.current,
estimateSize: () => 33,
overscan: 5,
})
<tbody
style={{
height: `${rowVirtualizer.getTotalSize()}px`,
position: 'relative',
}}
>
{rowVirtualizer.getVirtualItems().map(virtualRow => {
const row = rows[virtualRow.index]
return (
<tr
key={row.id}
style={{
position: 'absolute',
transform: `translateY(${virtualRow.start}px)`,
width: '100%',
}}
>
{row.getVisibleCells().map(cell => (
<td key={cell.id}>{/* render cell */}</td>
))}
</tr>
)
})}
</tbody>const rows = table.getRowModel().rows
const rowVirtualizer = useVirtualizer({
count: rows.length,
getScrollElement: () => tableContainerRef.current,
estimateSize: () => 33,
overscan: 5,
})
<tbody
style={{
height: `${rowVirtualizer.getTotalSize()}px`,
position: 'relative',
}}
>
{rowVirtualizer.getVirtualItems().map(virtualRow => {
const row = rows[virtualRow.index]
return (
<tr
key={row.id}
style={{
position: 'absolute',
transform: `translateY(${virtualRow.start}px)`,
width: '100%',
}}
>
{row.getVisibleCells().map(cell => (
<td key={cell.id}>{/* render cell */}</td>
))}
</tr>
)
})}
</tbody>The virtualized rows examples show how to render large row counts while keeping the DOM small. The examples are available for React, Solid, Svelte, Vue, Angular, and Lit.
The core idea is that sorting, filtering, grouping, and other row-model work still comes from TanStack Table. The virtualizer reads from the final table row model:
const rows = table.getRowModel().rowsconst rows = table.getRowModel().rowsThe row virtualizer is configured with count: rows.length, a row height estimate, the scroll container, and an overscan value. The tbody is given the full virtual height with rowVirtualizer.getTotalSize(), while each rendered row is absolutely positioned with transform: translateY(...).
The examples render cells from the current row with APIs like row.getVisibleCells() or row.getAllCells(), depending on whether the example needs visibility-aware cells or all cells.
The official examples use large generated datasets, commonly tens or hundreds of thousands of rows. They also support dynamic row heights by using measureElement when possible. The examples skip dynamic row measurement in Firefox because Firefox can measure table border height differently.
The virtualized columns examples show how to render large row and column counts. The examples are available for React, Solid, Svelte, Vue, Angular, and Lit.
Column virtualization uses the current visible column list:
const visibleColumns = table.getVisibleLeafColumns()const visibleColumns = table.getVisibleLeafColumns()The column virtualizer is configured for horizontal virtualization:
const columnVirtualizer = useVirtualizer({
count: visibleColumns.length,
estimateSize: index => visibleColumns[index].getSize(),
getScrollElement: () => tableContainerRef.current,
horizontal: true,
overscan: 3,
})const columnVirtualizer = useVirtualizer({
count: visibleColumns.length,
estimateSize: index => visibleColumns[index].getSize(),
getScrollElement: () => tableContainerRef.current,
horizontal: true,
overscan: 3,
})Column virtualization uses a different rendering strategy than row virtualization. Instead of absolutely positioning columns, the examples add fake spacer cells to the left and right:
const virtualColumns = columnVirtualizer.getVirtualItems()
const virtualPaddingLeft = virtualColumns[0]?.start ?? 0
const virtualPaddingRight =
columnVirtualizer.getTotalSize() -
(virtualColumns[virtualColumns.length - 1]?.end ?? 0)const virtualColumns = columnVirtualizer.getVirtualItems()
const virtualPaddingLeft = virtualColumns[0]?.start ?? 0
const virtualPaddingRight =
columnVirtualizer.getTotalSize() -
(virtualColumns[virtualColumns.length - 1]?.end ?? 0)Those spacer cells preserve the horizontal scroll width while the renderer only mounts the virtual columns. This approach keeps row rendering table-like and allows dynamic row height measurement to keep working.
The official virtualized columns examples also virtualize rows. In those examples:
Always use virtual indexes against the same current row and column lists returned by the table. If sorting, filtering, pagination, grouping, or column visibility changes, recompute the virtualized rows and columns from the current table state.
The virtualized infinite scrolling examples combine row virtualization with progressive data fetching. The examples are available for React, Solid, Svelte, Vue, Angular, and Lit.
The common pattern is:
The React example uses TanStack Query's useInfiniteQuery, but the same pattern works with any data-fetching layer.
const { scrollHeight, scrollTop, clientHeight } = scrollElement
if (scrollHeight - scrollTop - clientHeight < 500) {
fetchNextPage()
}const { scrollHeight, scrollTop, clientHeight } = scrollElement
if (scrollHeight - scrollTop - clientHeight < 500) {
fetchNextPage()
}If sorting is handled by the server, use manual sorting so the fetched data reflects the whole backend dataset rather than only the currently loaded rows. When sorting changes and the fetched dataset is replaced, scroll back to the top with rowVirtualizer.scrollToIndex(0).
Dynamic row heights are useful when content can wrap or expand. They are also more complex than fixed-height rows.
Use estimateSize as the virtualizer's initial guess:
estimateSize: () => 33estimateSize: () => 33Then use measureElement to refine the actual row height after rendering:
<tr
data-index={virtualRow.index}
ref={node => rowVirtualizer.measureElement(node)}
><tr
data-index={virtualRow.index}
ref={node => rowVirtualizer.measureElement(node)}
>Set data-index on each row so the virtualizer can associate measurements with the correct item. In non-React adapters, call measureElement through the adapter-appropriate ref, action, directive, or controller.
Overscan helps avoid blank regions while measurements settle. If every row has a known fixed height, skip dynamic measurement and use the fixed height estimate instead.
The examples still use semantic table tags, but they change table layout CSS to support virtual positioning and sticky headers.
Dynamic row virtualization commonly requires:
table {
display: grid;
}
thead {
display: grid;
position: sticky;
top: 0;
}
tr {
display: flex;
}table {
display: grid;
}
thead {
display: grid;
position: sticky;
top: 0;
}
tr {
display: flex;
}Rows are absolutely positioned inside a relatively positioned tbody, and cells use flex sizing so they can match column.getSize() or cell.column.getSize(). This is intentional. Native table layout does not work well with dynamic-height virtual rows that are positioned independently.
The React examples include Virtualized Rows Experimental and Virtualized Columns Experimental. These examples are advanced experiments for reducing React render work during scroll.
Use the standard examples first. Reach for the experimental examples only after profiling shows that React render work during scroll is the bottleneck.
The experimental examples use TanStack Virtual's onChange callback to imperatively update DOM styles instead of passing every scroll-position change through React render.
The experimental row example:
onChange: instance => {
instance.getVirtualItems().forEach(virtualRow => {
const rowRef = rowRefsMap.current.get(virtualRow.index)
if (!rowRef) return
rowRef.style.transform = `translateY(${virtualRow.start}px)`
})
}onChange: instance => {
instance.getVirtualItems().forEach(virtualRow => {
const rowRef = rowRefsMap.current.get(virtualRow.index)
if (!rowRef) return
rowRef.style.transform = `translateY(${virtualRow.start}px)`
})
}The experimental column example also mutates scroll-position-only DOM styles:
tableContainerRef.current?.style.setProperty(
'--virtual-padding-left',
`${virtualPaddingLeft}px`,
)
tableContainerRef.current?.style.setProperty(
'--virtual-padding-right',
`${virtualPaddingRight}px`,
)
tableBodyRef.current!.style.height = `${instance.getTotalSize()}px`tableContainerRef.current?.style.setProperty(
'--virtual-padding-left',
`${virtualPaddingLeft}px`,
)
tableContainerRef.current?.style.setProperty(
'--virtual-padding-right',
`${virtualPaddingRight}px`,
)
tableBodyRef.current!.style.height = `${instance.getTotalSize()}px`It updates row transforms through DOM refs and memoizes header and cell components while the column virtualizer is scrolling.
Because these examples update the DOM outside React's normal render flow, keep the imperative updates narrowly scoped to scroll-position-only styles like transform, body height, and spacer widths. Do not use this pattern for business state, table state, data, sorting, filtering, or cell values.
| Need | Start with |
|---|---|
| Many rows, normal columns | Virtualized Rows |
| Many columns | Virtualized Columns |
| Many rows and columns | Virtualized Columns |
| Remote data loaded as the user scrolls | Virtualized Infinite Scrolling |
| React scroll performance after profiling | Experimental React examples |