Top Free Open-Source React Data Grid Libraries

Most React data grid libraries can display tabular data, but they differ in what happens after your application grows. Features such as virtualization, advanced editing, AI-assisted development, extensibility, and licensing can have a significant impact on both development effort and future maintenance. Choosing the wrong library often means working around limitations or planning a costly migration later.

This article compares the leading free and open-source React data grid libraries to help you identify the best option for your application's requirements.

What Is a React Data Grid?

A React data grid is a UI component for displaying, editing, filtering, sorting, grouping, and managing large datasets in React applications. Unlike a basic HTML table, a React data grid typically includes advanced capabilities such as virtualization, column management, row selection, inline editing, data export, and server-side data handling.

React data grids typically include features such as:

• Virtualization to render only visible rows and columns for better performance with large datasets.
• In-cell editing for updating data directly within grid cells.
• Sorting and filtering for organizing and searching data.
• Row grouping and tree data for working with hierarchical datasets.
• Pagination and infinite scrolling for handling large volumes of data.
• Data export to formats such as CSV, Excel, and PDF.
• Custom cell renderers for displaying React components, charts, buttons, badges, and other interactive content.
• Column management features such as resizing, reordering, pinning, and visibility controls.

React data grids are commonly used in dashboards, admin panels, CRM systems, ERP platforms, financial applications, reporting tools, and other data-heavy web applications.

The following are the top free and open-source React data grid libraries for building data-intensive applications.

1. LyteNyte Grid

LyteNyte Grid is an open-source React data grid designed for applications that need high performance, advanced data operations, and extensive customization. It supports both headless and pre-styled implementations, allowing developers to either build a completely custom interface or use built-in themes to accelerate development.

The grid uses a fully stateless, prop-driven architecture that works with React state, URL parameters, server state, and external state management solutions. It also includes AI Skills that provide coding agents with extensive knowledge about the grid's APIs, and implementation patterns to help developers generate complex data grid implementations using natural language prompts.

LyteNyte Grid is built with TypeScript, supports the latest React applications, and focuses heavily on performance. According to the vendor, the grid is approximately 40 KB gzipped, can render millions of rows, process up to 10,000 updates per second, and delivers performance improvements of up to 7× compared to competing grids.

Developers can start with the LyteNyte Grid Core plan, which is completely free, before purchasing the PRO version with a production license. This makes it easy to determine whether LyteNyte Grid is one of the best React grids for your project before committing to a paid plan. LyteNyte Grid Core is ideal for individuals, hobbyists, and open-source teams.

Key Features

Below are the key features of LyteNyte Grid:

• AI-powered development workflows - Includes AI Skills that provide coding agents such as Claude Code, Cursor, Windsurf, and Codex with deeper knowledge about LyteNyte Grid APIs, components, configuration patterns, theming, and TypeScript usage.
• Stateless and prop-driven architecture - Uses a fully controlled architecture that integrates with React state, URL parameters, server state, and external state management solutions without the need for synchronization.
• Headless and pre-styled implementations - Supports fully headless development for complete UI control while also providing pre-built themes and styling options for faster implementation.
• Advanced data loading strategies - Supports client-side datasets, server-side pagination, infinite scrolling, and viewport-based loading for large-scale applications.
• High-performance data processing - Designed to render millions of rows, handle high-frequency data updates, and process large datasets efficiently while maintaining responsive user interfaces. According to tests done by the vendor it records:
  • Fast dataset updates - Reached 51 FPS in the vendor's cell-update (full dataset replacement) benchmark.
  • Smooth scrolling at scale - The only grid to maintain a consistent 60 FPS while scrolling across up to one million rows.
  • Efficient filtering - Sustained around 45 FPS when filtering 100,000 rows in the vendor's benchmarks.
  • Low memory footprint - Recorded among the lowest memory usage of the grids tested while sustaining high frame rates.
• Comprehensive column management - Includes column resizing, autosizing, reordering, pinning, visibility controls, grouping, spanning, floating headers.
• Advanced row and hierarchy support - Supports row selection, row pinning, row dragging, row master-detail views, row grouping, aggregations, and hierarchical datasets.
• Cell editing and data entry tools - Includes inline editing, full-row editing, edit validation, linked cell updates, bulk editing, custom editors, and cell range selection.
• Filtering, search, and query capabilities - Supports text, number, date, and set-based filtering, quick search, and grouping filters.
• Aggregation and summaries - Provides built-in aggregation functions and calculated summaries for analytical workloads. (Pivot tables and data reshaping are available in LyteNyte Grid PRO.)
• Data export and clipboard operations - Supports exporting data to CSV, Excel, Parquet, and Arrow formats, along with clipboard copy-and-paste operations and custom export workflows.
• Type-safe extensibility - Built with TypeScript and supports extending APIs, column definitions, and component configurations with custom properties and methods.
• Accessibility and internationalization - Supports WAI-ARIA accessibility standards, keyboard navigation, touch interactions, screen readers, and right-to-left (RTL) rendering.
• Flexible styling integrations - Supports vanilla CSS, Tailwind CSS, CSS Modules, Emotion, and custom styling approaches. Themes are shipped as separate CSS files, allowing applications to include only the styles they use and reduce CSS bundle size.

Let's see how simple it's to display a table using Lytenyte core.

import "@1771technologies/lytenyte-core/light-dark.css";
import { Grid, useClientDataSource } from "@1771technologies/lytenyte-core";
interface Person {
  id: number;
  firstName: string;
  lastName: string;
  email: string;
}
const data: Person[] = [
  { id: 1, firstName: "Alice", lastName: "Johnson", email: "[email protected]" },
  { id: 2, firstName: "Michael", lastName: "Brown", email: "[email protected]" },
];
const columns: Grid.Column<{ data: Person }>[] = [
  { id: "id", name: "ID", width: 80, type: "number" },
  { id: "firstName", name: "First Name" },
  { id: "lastName", name: "Last Name" },
  { id: "email", name: "Email", widthFlex: 1 },
];
export default function App() {
  const rowSource = useClientDataSource<Person>({ data });
  return (
    <div className="ln-grid" style={{ height: 300 }}>
      <Grid columns={columns} rowSource={rowSource} />
    </div>
  );
}

2. TanStack Table

TanStack Table is a free open-source React data grid library that uses a headless architecture to separate table functionality from the user interface. This approach makes it a common choice for applications that require custom designs and specific user interface requirements.

The library is distributed under the MIT license, with all functionality available in the free open-source version. TanStack Table uses a framework-agnostic core and provides adapters for React, Vue, Angular, Svelte, Solid, Qwik, Lit, Alpine, and Vanilla JavaScript. The React adapter supports React 16.8 through React 19.

TanStack Table is written in TypeScript, although TypeScript is optional for implementation. It is also one of the most widely adopted table libraries in the JavaScript ecosystem, with more than 1.6 billion total downloads, nearly 18 million weekly downloads, and over 28,000 GitHub stars.

Key Features

Below are the key features of TanStack Table:

• Headless architecture - Provides the data grid engine without pre-built UI components, giving developers full control over markup, styling, accessibility, and interactions.
• Fully controlled state management - Let developers manage table state such as sorting, filtering, pagination, row selection, and column visibility within their own React application.
• Flexible column definitions and rendering - Supports accessor functions, grouped columns, custom cell renderers, custom headers and footers, and column metadata for building highly customized table layouts.
• Client-side and server-side operations - Supports browser-based or backend-driven processing for data-intensive operations.
• Advanced column and row management - Includes column ordering, pinning, resizing, visibility controls, row pinning, and row selection for building customizable table layouts.
• Grouping and aggregation - Supports grouping records by one or more columns and calculating aggregate values such as sums, counts, averages, minimums, and maximums.
• Hierarchical and expandable data - Supports nested rows, expandable records, child rows, and detail panels for working with hierarchical datasets.
• Faceted filtering - Supports column filtering, global filtering, column faceting, and global faceting for building advanced search and filtering experiences.
• Virtualization support - Integrates with virtualization libraries such as TanStack Virtual and react-window to efficiently render large datasets.
• React-specific adapter - Provides React hooks and rendering utilities for integrating the TanStack Table core with React applications.
• Framework-agnostic core - Uses the same table engine across React, Vue, Angular, Svelte, Solid, Qwik, Lit, Alpine, and Vanilla JavaScript.
• Framework and styling flexibility - Works with CSS, CSS-in-JS, Tailwind, component libraries, and custom design systems without imposing a specific styling approach.
• TypeScript support - Written in TypeScript with strong type inference for rows, columns, and cells. TypeScript is optional, but it helps improve autocomplete and reduce development errors.

Here is a code example of how to use Tanstack. Out of the box, TanStack Table's example looks more primitive because it's headless. It provides only the table logic and leaves all markup and styling to you.

import {
  useReactTable,
  getCoreRowModel,
  flexRender,
  type ColumnDef,
} from "@tanstack/react-table";
interface Person {
  id: number;
  firstName: string;
  lastName: string;
  email: string;
}
const data: Person[] = [
  { id: 1, firstName: "Alice", lastName: "Johnson", email: "[email protected]" },
  { id: 2, firstName: "Michael", lastName: "Brown", email: "[email protected]" },
];
const columns: ColumnDef<Person>[] = [
  { accessorKey: "id", header: "ID" },
  { accessorKey: "firstName", header: "First Name" },
  { accessorKey: "lastName", header: "Last Name" },
  { accessorKey: "email", header: "Email" },
];
export default function App() {
  const table = useReactTable({
    data,
    columns,
    getCoreRowModel: getCoreRowModel(),
  });
  return (
    <table>
      <thead>
        {table.getHeaderGroups().map((hg) => (
          <tr key={hg.id}>
            {hg.headers.map((header) => (
              <th key={header.id}>
                {flexRender(header.column.columnDef.header, header.getContext())}
              </th>
            ))}
          </tr>
        ))}
      </thead>
      <tbody>
        {table.getRowModel().rows.map((row) => (
          <tr key={row.id}>
            {row.getVisibleCells().map((cell) => (
              <td key={cell.id}>
                {flexRender(cell.column.columnDef.cell, cell.getContext())}
              </td>
            ))}
          </tr>
        ))}
      </tbody>
    </table>
  );
}

3. AG Grid

AG Grid is a free open-source React data grid designed for building data-intensive web applications. It provides a fully featured grid engine with no third-party dependencies and supports React, Angular, Vue, and JavaScript applications.

AG Grid Community is available under the MIT license and can be used in production at no cost and with no license needed, while AG Grid Enterprise offers additional commercial features and a 30-day trial for evaluation.

AG Grid is one of the most widely adopted data grid libraries in the industry, with more than 5 million weekly npm downloads, over 15,000 GitHub stars, and usage across 90% of Fortune 500 companies. It is actively maintained with regular releases and supports modern desktop and mobile browsers, including Chrome, Firefox, Edge, Safari, iOS Safari, and Android Chrome.

For React developers, AG Grid supports React 16.8 through React 19 by making it compatible with both existing applications and modern React projects.

Key Features

• MCP server integration - Provides an MCP (Model Context Protocol) server that supplies AI coding assistants (LLM optimized search tool) with version-specific documentation, examples, API references, migration guidance, and implementation resources for AG Grid development.
• Advanced filtering - Supports text, number, BigInt, and date filtering, along with Excel-style set filters. Developers can also create custom filter components to match application requirements.
• Customizable sorting - Includes built-in column sorting with support for custom comparator functions, per-column sorting controls, and application-specific sorting logic.
• Cell editing framework - Supports editable cells, conditional editing rules, data-type-aware editors, full-row editing workflows, and editing lifecycle events for tracking data changes.
• CSV data export - Exports grid data to CSV while supporting value getters, value formatters, grouped data exports, and configurable export processing.
• Drag-and-drop interactions - Supports row reordering, column movement, grid-to-grid interactions, and integration with native browser drag-and-drop workflows.
• Built-in themes and styling - Includes Quartz, Alpine, Balham, and Material themes, along with CSS variables and theming APIs for custom grid styling.
• Row selection controls - Supports single-row and multi-row selection through mouse, keyboard, and API-driven interactions.
• Accessibility support - Implements ARIA attributes, keyboard navigation, screen reader compatibility, high-contrast theming, and guidance for WCAG, ADA, and Section 508 compliance.
• Infinite scrolling - Loads data incrementally as users scroll, helping applications work with large datasets without loading all records into the browser at once.
• Row pagination - Supports client-side pagination across multiple row models and provides customizable pagination controls and styling options.
• Server-side data loading - Supports lazy loading, server-side filtering, sorting, and large dataset management through server-driven data retrieval.
• Custom cell components - Allows developers to render custom HTML, links, buttons, images, interactive controls, and reusable cell components directly within grid cells.

Let's have a look at a simple code on how to use AG grid.

import { AgGridReact } from "ag-grid-react";
import {
  AllCommunityModule,
  ModuleRegistry,
  type ColDef,
} from "ag-grid-community";
ModuleRegistry.registerModules([AllCommunityModule]);
interface Person {
  id: number;
  firstName: string;
  lastName: string;
  email: string;
}
const rowData: Person[] = [
  { id: 1, firstName: "Alice", lastName: "Johnson", email: "[email protected]" },
  { id: 2, firstName: "Michael", lastName: "Brown", email: "[email protected]" },
];
const columnDefs: ColDef<Person>[] = [
  { field: "id", headerName: "ID", width: 90 },
  { field: "firstName", headerName: "First Name" },
  { field: "lastName", headerName: "Last Name" },
  { field: "email", headerName: "Email", flex: 1 },
];
export default function App() {
  return (
    <div style={{ height: 300, width: "100%" }}>
      <AgGridReact rowData={rowData} columnDefs={columnDefs} />
    </div>
  );
}

4. MUI X Data Grid

MUI X Data Grid is a React-first data grid component built on top of the MUI ecosystem. Unlike headless libraries, it ships with a fully styled user interface, built-in accessibility features, and ready-to-use functionality for common data grid requirements.

The Data Grid is part of MUI X's open-core product lineup. The Community edition is MIT-licensed and free forever, while Pro and Premium plans add advanced capabilities for larger datasets and analytics workloads. MUI X integrates directly with Material UI, making it a natural choice for teams already using the MUI design system, although it can also be customized to work with other design systems.

The project is actively maintained by the MUI team and supported by a large open-source community, with more than 5.8 million weekly npm downloads, nearly 94,000 GitHub stars, and over 3,000 contributors. Developers can also evaluate Pro and Premium features for up to 30 days in non-production environments before purchasing a commercial license.

Key Features

• Fully styled React data grid - Provides a production-ready user interface with built-in accessibility, theming, pagination controls, filtering menus, and editing experiences without requiring developers to build grid components from scratch.
• Built-in editing and CRUD operations - Supports inline cell editing, row editing, and create, read, update, and delete (CRUD) operations. Columns can be configured as editable, and editing can be controlled at both cell and row levels.
• Filtering and sorting - Includes column filtering, quick filtering across multiple columns, and column sorting with built-in user interface controls.
• Pagination support - Provides built-in client-side pagination controls for navigating large datasets without implementing custom paging components.
• Column grouping - Supports multi-level column hierarchies with nested column groups, custom group headers, tooltips, styling options, and configurable group header sizing.
• Column visibility management - Lets users show or hide columns through built-in menus while allowing developers to lock specific columns from being hidden.
• State persistence - Supports exporting and restoring grid state, including active filters, sorting configurations, and other user preferences.
• Column virtualization - Renders only visible columns during horizontal scrolling to improve performance when working with hundreds or thousands of columns.

MUI X Data Grid is easy to work with and comes fully styled out of the box.

import { DataGrid, type GridColDef, type GridRowsProp } from "@mui/x-data-grid";
const rows: GridRowsProp = [
  { id: 1, firstName: "Alice", lastName: "Johnson", email: "[email protected]" },
  { id: 2, firstName: "Michael", lastName: "Brown", email: "[email protected]" },
];
const columns: GridColDef[] = [
  { field: "id", headerName: "ID", width: 90 },
  { field: "firstName", headerName: "First Name", width: 160 },
  { field: "lastName", headerName: "Last Name", width: 160 },
  { field: "email", headerName: "Email", flex: 1 },
];
export default function App() {
  return (
    <div style={{ height: 300, width: "100%" }}>
      <DataGrid rows={rows} columns={columns} />
    </div>
  );
}

5. React-data-grid (Comcast)

React Data Grid (Comcast) is an open-source React data grid component built specifically for React and TypeScript applications. It supports React 19.2+, server-side rendering, evergreen browsers, and has no external dependencies, helping keep bundle sizes small. This focuses heavily on performance through row and column virtualization, while also providing built-in accessibility, light/dark theme support, and extensive customization options.

It is widely used by developers who want a lightweight grid without the licensing restrictions of commercial alternatives.

Key Features

• Lightweight Architecture - Supports tree-shaking, has no external dependencies, supports server-side rendering, and helps keep bundle sizes small.
• High-Performance Virtualization - Uses row and column virtualization so only visible content is rendered, improving performance for large datasets.
• TypeScript Support - Strictly typed with TypeScript, providing type safety for rows, columns, editors, events, and custom components.
• Accessibility and Theme Support - Includes keyboard accessibility, light and dark themes, and built-in RTL support for international applications.
• Column Management - Supports frozen columns, column resizing, column spanning, and nested column grouping for organizing complex datasets.
• Sorting and Selection - Supports multi-column sorting, single-row selection, and multi-row selection with keyboard navigation.
• Row Organization - Supports row grouping through TreeDataGrid, pinned summary rows, dynamic row heights, and custom empty-state content when no data is available.
• Cell Editing and Spreadsheet Operations - Supports inline editing, custom editors, validation logic, clipboard copy/paste, and drag-to-fill operations similar to spreadsheet applications.
• Flexible Rendering and Customization - Supports custom cell formatting and allows developers to replace cells, rows, checkboxes, editors, and other UI elements with custom React components.

The code sample below defines the columns and rows, then passes them to the DataGrid component. Note the stylesheet import on the first line.

import "react-data-grid/lib/styles.css";
import { DataGrid, type Column } from "react-data-grid";
interface Row {
  id: number;
  firstName: string;
  lastName: string;
  email: string;
}
const columns: readonly Column<Row>[] = [
  { key: "id", name: "ID", width: 80 },
  { key: "firstName", name: "First Name" },
  { key: "lastName", name: "Last Name" },
  { key: "email", name: "Email" },
];
const rows: readonly Row[] = [
  { id: 1, firstName: "Alice", lastName: "Johnson", email: "[email protected]" },
  { id: 2, firstName: "Michael", lastName: "Brown", email: "[email protected]" },
];
export default function App() {
  return <DataGrid columns={columns} rows={rows} />;
}

6. RevoGrid

RevoGrid is a TypeScript-based react-data-grid and built with StencilJS for data-intensive applications. The open-source core is designed to handle large datasets efficiently through virtualization, intelligent DOM updates, and a lightweight architecture with minimal bundle size. It includes accessibility support, RTL compatibility, Excel-like keyboard interactions, flexible customization options, and a plugin-based architecture for extending grid functionality without replacing the core grid.

Renders 1M+ rows, millions of cells, and thousands of columns with no hard row limit. Virtualization keeps rendering focused on visible content to maintain performance with large datasets.

Key Features

Below are the key features of RevoGrid react grid library:

• Accessibility and Internationalization - Follows WAI-ARIA best practices, provides comprehensive RTL support, and includes keyboard-first navigation and editing with Excel-like interactions and spreadsheet copy/paste support.
• Lightweight Architecture - Maintains a small bundle size with support for module-based imports and polyfills for broader browser compatibility.
• Drag and Drop - Supports drag-and-drop interactions for both rows and columns.
• Sorting and Filtering - Includes configurable sorting, predefined filters, multi-column filtering, conditional filters, header filters, selection filters, slider filters, collection preservation, and custom filter extensions.
• Data Export - Supports built-in CSV export and browser-side PDF export through the lightweight @revolist/revogrid-pdf-export plugin.
• Column and Row Management - Supports custom column and row sizes, column resizing, automatic column sizing, pinned columns, and pinned rows.
• Grouping and Data Organization - Supports nested column headers, row grouping, column grouping drill-down, trimmed rows, and built-in column types including text, number, date, dropdown, and custom types.
• Range Selection and Editing - Supports multi-cell selection and editing workflows across cell ranges.
• Themes and Styling - Includes Excel-style themes by default, along with Material Design themes in compact, dark, and light variants.
• Extensibility and Plugins - Supports VNode features, TSX-based customization, custom plugins, and extension of existing functionality.
• Flexible Customization - Supports custom column headers, row headers, cell properties, cell templates, and custom cell editors.
• AI Agents and MCP Integration - Connects Codex, Cursor, Claude Code, and VS Code to version-aware documentation, examples, migrations, feature availability information, and typed API references.
• Rich API Support - Provides extensive APIs and hundreds of additional configuration options for customizing grid behavior and user interactions.

Now let's see what a basic RevoGrid setup looks like in practice.

import { useState } from "react";
import { RevoGrid } from "@revolist/react-datagrid";
const columns = [
  { prop: "id", name: "ID", size: 80 },
  { prop: "firstName", name: "First Name" },
  { prop: "lastName", name: "Last Name" },
  { prop: "email", name: "Email" },
];
export default function App() {
  const [source] = useState([
    { id: 1, firstName: "Alice", lastName: "Johnson", email: "[email protected]" },
    { id: 2, firstName: "Michael", lastName: "Brown", email: "[email protected]" },
  ]);
  return <RevoGrid columns={columns} source={source} />;
}

Bundle Size and Licensing Comparison

Bundle size and licensing are two important factors when comparing React data grids. Bundle size affects the amount of code added to your application, which can influence initial load times and overall frontend performance. Licensing determines which features are available in the free version and whether advanced capabilities require a commercial subscription.

Among the grids compared, LyteNyte Grid stands out for combining a relatively small bundle size with a broad set of built-in features. This makes it a strong option for developers looking for the best react grid without sacrificing performance or functionality. As always, the right choice depends on your application's requirements, feature needs, and budget.

Bundle Size

Licensing

Detailed Feature Comparison

This comparison focuses only on features available in the free or open-source editions of each React data grid library. Paid-only capabilities available in AG Grid Enterprise, MUI X Pro/Premium, RevoGrid Pro, or other commercial editions are not included.

To help interpret the comparison results, the following definitions explain what each value in the table means:

• Yes = The feature is available in the free or open-source version out of the box.
• No = The feature is not available in the free version or requires a paid plan.
• Custom = The feature is supported, but the library provides the underlying APIs and logic rather than a ready-to-use implementation. Developers need to build part of the UI or behavior themselves.
• Limited = The feature exists, but with restrictions compared to other grids. It may support basic scenarios but lack some advanced capabilities.

Other Noteworthy Options

In addition to the React data grid libraries covered above, there are several other options worth evaluating depending on your project requirements.

PrimeReact DataTable - A feature-rich React data table that includes pagination, sorting, filtering, row and column grouping, row expansion, inline editing, row and cell selection, virtual scrolling, frozen rows and columns, column resizing, column reordering, CSV export, context menus, and state persistence. It is a strong choice for applications already built on the PrimeReact ecosystem and is available under the MIT license.

Frequently Asked Questions

What Is the Difference Between a React Data Grid and a React Table?

A React data grid includes advanced functionality such as virtualization, filtering, editing, grouping, column management, and large dataset support. A React table typically focuses on displaying tabular data and often requires additional libraries or custom development to support advanced data management features.

How Do You Choose the Best React Data Grid for Large Datasets?

The best React data grid for large datasets should support virtualization, efficient rendering, server-side data loading, and responsive scrolling. These features help maintain performance when working with thousands or millions of rows while minimizing browser memory usage.

What Features Should a React Data Grid Component Include?

A React data grid component should support sorting, filtering, row selection, editing, pagination, virtualization, and customization options. Depending on the application, additional capabilities such as grouping, tree data, data export, and custom cell renderers may also be important.

When Should You Use an Open-Source React Data Grid Instead of a Commercial Grid?

An open-source React data grid is often the right choice when the required features are available without a commercial license and the development team has the resources to customize or extend the grid. Commercial grids may be a better fit when advanced enterprise features, dedicated support, or compliance requirements are critical.

Which Is the Best React Data Grid for Custom User Interfaces?

There is no single best React data grid for every project. The right choice depends on factors such as customization requirements, built-in features, performance, licensing, and long-term maintenance. For applications that require extensive UI customization, options such as LyteNyte Grid, TanStack Table, and other highly configurable solutions are often considered among the best React table and data grid choices because they provide greater control over styling and user experience.