SvGrid vs @vincjo/datatables

@vincjo/datatables is a great minimal pick when you want to keep your own table markup and just need sort / filter / paginate. SvGrid is the fuller grid - virtualization, Excel filters, editing, a render component - for heavier apps.

@vincjo/datatables gives you a small, ergonomic handler that wraps your data with reactive sorting, filtering, and pagination while you keep full control of the markup. It is MIT-licensed and popular for its simplicity.

SvGrid scales further up the curve: it keeps a headless engine but also ships a virtualized render component, an Excel-style filter menu, inline editing, cell selection, and an imperative API - for when a hand-rolled table stops being enough.

Looking for a @vincjo/datatables alternative for Svelte?

It is a helper for your own markup rather than a grid, which is exactly right until you need virtualization, inline editing or column pinning and start building them yourself. Moving to SvGrid keeps the headless option and adds those. If your table is a few hundred rows of your own HTML, staying put is the smaller dependency.

Migration guide: moving from @vincjo/datatables to SvGrid

SvGrid vs @vincjo/datatables: feature by feature

Feature	SvGrid	@vincjo/datatables
Svelte native	✅	✅
Render component	✅ <SvGrid />	❌ BYO markup
Virtualization	✅	❌
Excel-style filters	✅	⚠️ Basic filtering
Inline editing	✅	❌ BYO
Cell selection + copy	✅	❌ BYO
Grouping / tree / master-detail	✅	❌
Footprint for a simple table	⚠️ Larger	✅ Tiny
AI / MCP integration	✅	❌

What they have in common

Svelte-native, not a port.
Headless-friendly: you can drive your own markup.
MIT-licensed.
Client- and server-side data modes.

Where SvGrid is stronger

Built-in virtualized render component - no need to author the table.
Excel-style filter menu, inline editing, and cell-range selection.
Row + column virtualization for large datasets.
Imperative SvGridApi + @svgrid/mcp MCP server.
Optional Enterprise pack for export, import, pivot, and AI.

Where @vincjo/datatables is stronger

Much smaller surface and bundle if all you need is sort / filter / paginate.
You keep 100% control of the table markup with zero render opinions.
Faster to learn for a simple table.

Choose SvGrid when

You need virtualization, editing, or Excel-style filtering.
You want a render component instead of hand-authoring the table.
You expect the grid to grow into grouping, tree, or master/detail.

Choose @vincjo/datatables when

You only need sort / filter / paginate over a small dataset.
You want to keep full control of your own table markup.
You want the smallest possible bundle for a simple table.

The bottom line

For a small sort/filter/paginate list you keep full control over, @vincjo/datatables is delightfully light. The moment you need virtualization, Excel-style filters, editing, or grouping, SvGrid is the grid that already has them.

Frequently asked questions

SvGrid vs @vincjo/datatables - which to pick?

Pick @vincjo/datatables for a small, markup-controlled table; pick SvGrid when you need virtualization, editing, filters, or grouping. Both are MIT and Svelte-native.

Is @vincjo/datatables lighter than SvGrid?

Yes, for a simple table it is smaller. SvGrid carries more because it ships a virtualized render component and a full feature set.

Can SvGrid be headless like @vincjo/datatables?

Yes - its headless core lets you keep your own markup, the same way @vincjo/datatables does.