React DataGrid: A Free, Open-Source React Data Grid with an Enterprise Edition (An AG Grid Alternative)

If you've ever needed to build a serious data table in React, you've probably run into this problem. React doesn't include a native data grid component, so you're usually left choosing between paying for an enterprise solution or spending weeks building advanced table functionality yourself.

For small datasets, a simple HTML table works well enough. But once you need virtualization, row grouping, inline editing, advanced filtering, server-side data loading, or richer keyboard interactions, things become much more complicated. Those features require significant engineering effort if you decide to build everything from scratch.

That's exactly where React DataGrid, an open-source React data grid with both free and Enterprise offerings, comes in.

In this article, I'll walk through what makes a production-ready React data grid, introduce React DataGrid, show how to get started with its open-source edition, explore its standout features, explain what's available in the Enterprise edition, and compare it with AG Grid so you can decide which option is right for your project.

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TL;DR

If you're looking for a React data grid that combines an open-source MIT-licensed core with an optional Enterprise edition, React DataGrid is worth considering.

It's an open-source React data grid built with React 18, TypeScript, and Tailwind CSS, designed for everything from simple data tables to large, data-intensive applications. The free edition provides a broad set of data-grid capabilities, while the Enterprise edition adds commercial features for teams that need more advanced workflows, data operations, and enterprise functionality.

Here's what React DataGrid offers:

✅ MIT-licensed, open-source core that is free to use.
✅ Virtual scrolling for datasets with 100,000+ rows and 200+ columns.
✅ Server-side infinite scrolling for datasets with 100M+ rows, including server-side filtering, sorting, pagination, intelligent block caching, request concurrency, and LRU cache eviction.
✅ Row grouping and aggregation for organizing and analyzing complex datasets.
✅ Tree Data for hierarchical rows and expandable parent-child structures.
✅ Market data support for applications that receive frequent live updates.
✅ 10 built-in themes, custom cell renderers, layout persistence, density modes, and extensive customization APIs.
✅ Accessibility support with WCAG 2.1 AA compliance and a published VPAT 2.4 report.
✅ Enterprise features including Server-Side Row Model, Master/Detail, Formula Engine, Undo/Redo, Range Selection, Clipboard (TSV), Fill Handle, Transactions, Cell Permissions, Audit Trail, Row Locking, Excel/CSV Import, PDF Export, Filter Presets, Saved Views, and Form Editor.
✅ A familiar AG Grid-style API that can make adoption easier for developers already working with enterprise data grid libraries.

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What Are React Data Grid Components?

A React data grid component is a specialized table component designed to display and manage large, interactive datasets. Unlike a basic HTML table, it typically includes features such as sorting, filtering, pagination, row selection, inline editing, keyboard navigation, and virtualization.

A traditional HTML <table> is perfectly fine for displaying a few dozen rows of static data. The problem appears once datasets start growing or users need richer interactions.

Rendering thousands of rows can slow down the browser, and implementing advanced behaviors like filtering, editing, or drag-and-drop often means writing and maintaining a significant amount of custom code.

That's why most production React applications rely on dedicated data grid libraries. They solve performance challenges, provide a consistent user experience, and include many of the features that enterprise dashboards, admin panels, analytics platforms, and internal business applications depend on every day.

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What Features Really Matter in a React Data Grid?

The difference between a basic data table and a production-ready React data grid comes down to five areas: performance, data operations, server-side capabilities, accessibility, and customization. These are also the features that many free libraries either limit or don't offer at all.

When evaluating a React data grid, here are the capabilities that deserve the most attention:

• Performance at scale through virtual scrolling so tens of thousands of rows remain smooth to navigate.
• Advanced data operations like row grouping, aggregation, filtering, multi-column sorting, and inline editing.
• Server-side support for massive datasets using infinite scrolling, server-side filtering, sorting, and intelligent caching.
• Accessibility with keyboard navigation, screen-reader compatibility, and WCAG compliance.
• Customization through themes, custom cell renderers, layout persistence, and flexible APIs that fit your application's design system.

Many open-source React grids do one or two of these things well.

Performance might be excellent, but advanced grouping is missing. Another library may support editing but fall short when datasets become truly large.

React DataGrid was built to check every one of those boxes.

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Introducing React DataGrid

React DataGrid is an open-source React data grid built with React 18, TypeScript, Tailwind CSS, and Vite. Its open-source core is MIT licensed and published as the react-open-source-grid npm package, while the project also offers an Enterprise edition with additional commercial features. The API is intentionally familiar to developers who have previously worked with AG Grid, which can make the learning curve smaller.

React DataGrid is part of the broader GridEngine platform, which provides data grid solutions for different technologies and use cases.

One thing I particularly like is that the project doesn't expect you to install it blindly. Before writing any code, you can explore a public live demo, browse the documentation, and inspect the GitHub repository to see exactly what the library offers.

That transparency is valuable, especially when you're evaluating a component that may become the backbone of your application's data layer.

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Installation & Quick Start

Getting started with React DataGrid is straightforward. If you're starting a new React project or adding a data grid to an existing application, you can install the package and have a working grid running in just a few minutes.

The setup is intentionally minimal so you can focus on your data instead of configuration.

Install the package:

npm install react-open-source-grid

Then import the stylesheet:

import 'react-open-source-grid/dist/lib/index.css';

Finally, create your first grid:

import { DataGrid } from 'react-open-source-grid';
import type { Column, Row } from 'react-open-source-grid';

const columns: Column[] = [
  { field: 'id', headerName: 'ID', width: 70 },
  { field: 'name', headerName: 'Name', width: 180, editable: true },
];

const rows: Row[] = [
  { id: 1, name: 'John Doe' },
  { id: 2, name: 'Jane Smith' },
];

export default function App() {
  return (
    <DataGrid
      columns={columns}
      rows={rows}
    />
  );
}

From this simple starting point, you can gradually enable more advanced capabilities like grouping, virtual scrolling, custom renderers, server-side infinite scrolling, and layout persistence, while keeping the same underlying grid as your application grows.

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Core Features of React DataGrid

React DataGrid stands out among open-source React data grid libraries because it doesn't just offer a long feature checklist. The open-source core gives you a broad foundation for everyday data-intensive applications, while the Enterprise edition provides additional capabilities for more advanced workflows as your requirements evolve.

Let's look at the capabilities that make the biggest difference in real-world React applications.

Everyday Grid Features You'll Actually Use

Every data grid should make everyday interactions feel effortless, and React DataGrid's open-source core covers a broad set of essential capabilities without requiring additional plugins or a commercial license.

Out of the box, you get:

• Click-to-sort columns
• Per-column filtering with advanced filtering options
• Pagination with 10, 20, or 50 rows per page
• Drag-to-resize columns
• Drag-and-drop column reordering
• Sticky column headers
• Full keyboard navigation
• Single and multiple row selection
• Double-click inline editing
• Built-in quick filter for searching across the entire grid

Beyond those essentials, React DataGrid also includes several quality-of-life features that become valuable in larger applications. APIs such as rowStyle, rowClass, and getRowHeight make it easy to highlight overdue invoices, completed tasks, priority tickets, or any other rows that deserve extra visual attention.

React DataGrid live demo with filtering, sorting, and status badges

 

Row Grouping and Aggregation for Complex Data

Row grouping is one of those features that developers often don't realize they need until users ask for it. When datasets become more complex, grouping records by department, status, region, customer, or category makes analysis much easier than scrolling through hundreds or thousands of individual rows.

React DataGrid lets users simply drag a column into the grouping area to organize data into expandable groups. Beyond grouping itself, the library also supports aggregation footers at two different levels.

You can display subtotals for each individual group as well as a grand-total footer for the entire dataset, with built-in aggregation functions including:

• Sum
• Average
• Minimum
• Maximum
• Count

Both group-level and grid-level aggregation are included in the open-source grid. That's noteworthy because similar functionality is often associated with commercial data grid offerings.

Besides row grouping, React DataGrid also supports tree data, allowing you to display hierarchical datasets with expandable parent and child rows. This is useful for cases such as organizational charts, file explorers, category trees, or nested project structures.

React DataGrid Tree Data Demo for folder and file structure with nested directories

 

Built for Scale: Virtual Scrolling, Market Data, and Server-Side Infinite Data

Performance is often the first thing users notice when working with large datasets. A data grid can have every feature imaginable, but if scrolling feels sluggish or interactions lag, the overall experience quickly suffers.

React DataGrid tackles this challenge with two complementary approaches, depending on the size of your data.

For large datasets that can still live in the browser, the library supports virtual scrolling. Instead of rendering every row and column into the DOM, it only renders what's currently visible on screen.

This enables smooth performance with 100,000+ rows and more than 200 columns, while reducing rendering overhead and memory usage compared to rendering everything at once. The documentation also reports up to 100× faster rendering, 100× lower memory usage, and smooth 60 FPS scrolling in virtual mode.

React DataGrid Virtual Scrolling Demo with 100,000 rows & 200 columns

 

Performance isn't only about handling large datasets; it also matters when the data is constantly changing. React DataGrid includes support for real-time market data cases, making it suitable for applications that receive frequent live updates while remaining responsive.

If you're building financial dashboards, trading platforms, monitoring systems, or live analytics applications, the grid is designed to process continuous data updates while preserving smooth scrolling and a responsive user experience. This makes it a good option for applications where users need to monitor rapidly changing information without sacrificing performance.

React DataGrid live streaming updates Demo

 

For applications dealing with truly massive datasets, React DataGrid goes a step further with its free Server-Side Infinite Scroll capability. The InfiniteScrollDataGrid component works with a ServerSideDataSource to request only the data users actually need while scrolling, instead of loading millions of records into the browser at once.

This free server-side mode includes:

• Server-side filtering, sorting, and pagination
• Intelligent block caching
• Configurable request concurrency
• LRU cache eviction
• Efficient handling of datasets with 100 million or more rows

Despite all of those capabilities, the API is simple:

const dataSource = new ServerSideDataSource({
  blockSize: 100,

  getRows: async (request) => {
    const response = await fetch("/api/data", {
      method: "POST",
      body: JSON.stringify(request),
    });

    return response.json();
  },
});

Instead of forcing developers to build custom pagination or infinite loading logic, the component handles the heavy lifting while your backend simply returns the requested records.

For applications that need more advanced server-side data-management capabilities, React DataGrid also offers a separate Server-Side Row Model as part of its Enterprise features.

Enterprise Features for Advanced Workflows

React DataGrid also offers an Enterprise edition for teams that need capabilities beyond the open-source core.

The Enterprise tier adds a collection of advanced features designed for more sophisticated data workflows, including server-side data management, transactional editing, controlled access, auditability, data import and export, and advanced record management.

Some of the Enterprise features include:

• Server-Side Row Model for applications that need more advanced server-side data management and block-based data fetching for large datasets.
• Master/Detail for expanding records and displaying related or nested information.
• Formula Engine for Excel-style formulas directly inside grid cells.
• Undo/Redo for multi-step reversible edits.
• Range Selection for selecting Excel-style cell ranges.
• Clipboard (TSV) for copying and pasting tabular data with spreadsheet-style workflows.
• Fill Handle for dragging to fill or copy cell values across a range.
• Transactions for staged add, update, and remove operations.
• Cell Permissions for controlling per-cell editing and data visibility.
• Audit Trail for maintaining an immutable record of edits.
• Row Locking for collaborative workflows where specific rows need to be locked.
• Excel/CSV Import for mapping, validating, and coercing imported data.
• PDF Export for generating branded, paginated documents from grid data.
• Filter Presets with an AND/OR filter builder and reusable filtering configurations.
• Saved Views for storing personal or shared grid layouts.
• Form Editor for editing records through a dedicated slide-in form interface.

These features are particularly useful when a data grid starts acting as an interactive workspace for business operations.

For example, a financial application might use the Formula Engine and Range Selection for spreadsheet-like workflows, while a business application with stricter data controls could combine Transactions, Cell Permissions, Audit Trail, and Row Locking to provide more controlled data management.

The Enterprise edition therefore gives teams a path to move from a capable open-source data grid to a more advanced commercial data-management experience without having to replace the underlying grid technology.

The open-source core also includes several features that make day-to-day development easier, such as computed value getters, custom formatters, flexible column sizing, conditional cell styling, shared default column definitions, built-in tooltips, loading overlays, and "no rows" states.

Taken together, the open-source core and Enterprise edition give React DataGrid a broader range of capabilities while allowing teams to choose the level of functionality that matches their requirements.

Accessibility and Enterprise Compliance

Accessibility is an area where many open-source UI libraries still fall short. Keyboard navigation may be partially implemented, screen readers may receive limited support, and formal accessibility documentation is often missing altogether.

React DataGrid stands out by treating accessibility as a core feature, not just an afterthought.

The grid is WCAG 2.1 AA compliant and includes full keyboard navigation, ARIA support, and screen-reader compatibility. It also publishes a VPAT 2.4 accessibility report along with Section 508 documentation, making it much easier for organizations with accessibility requirements to evaluate React DataGrid before adopting it.

While individual developers certainly benefit from accessible components, this kind of documentation becomes more valuable in larger companies where procurement, legal, or compliance teams often review third-party dependencies before they're approved for production use.

Theming, Customization, and Developer Experience

A data grid rarely exists in isolation. It needs to blend naturally into the rest of your application's design system, support custom business logic, and remain flexible as requirements evolve.

React DataGrid provides 10 built-in themes, covering both light and dark interfaces, including Quartz, Alpine, Material, Nord, Dracula, Solarized (Light and Dark), Monokai, One Dark, and a standard Dark theme.

Theme switching is powered by CSS variables, making it easy to match the rest of your application without extensive styling work. Themes can be switched instantly while preserving consistent spacing, typography, and component styling.

React DataGrid theme system

 

Customization goes well beyond colors. The library also provides:

• A custom cell renderer framework for badges, progress bars, images, buttons, charts, and icons.
• A right-click context menu with actions like copy, export, pin/unpin, auto-size, hide columns, and filter by value.
• Layout persistence using localStorage, server storage, or user profile storage.
• Multiple density modes ranging from Ultra Compact to Comfortable.
• Value getters and formatters for computed columns.
• Conditional styling through cellStyle, cellClass, and cellClassRules.
• Shared column configuration with defaultColDef and built-in default sorting.
• Tooltips, loading overlays, and no-data overlays.
• Declarative column visibility for showing or hiding columns based on user roles or application state.

Beyond the getting-started guides, the project includes a documented Grid API with more than 100 methods, along with interactive examples demonstrating how those APIs work. Enterprise capabilities build on this foundation with additional functionality for advanced data workflows.

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How React DataGrid Compares to AG Grid

AG Grid Community is a solid open-source grid, but many of its most powerful capabilities, including row grouping, server-side data handling, pivoting, and several advanced data operations, are reserved for the commercial Enterprise edition.

React DataGrid takes a different approach by making many of those enterprise-style features available under the MIT license.

Here's a side-by-side comparison:

Feature	AG Grid Community	AG Grid Enterprise ($$)	React DataGrid Free	React DataGrid Enterprise ($$)
License	MIT	Commercial	MIT	Commercial
Virtual Scrolling	✅	✅	✅	✅
Tree Data	❌	✅	✅	✅
Row Grouping	❌	✅	✅	✅
Server-Side Infinite Scroll	❌	✅	✅ (100M+ rows)	✅
Server-Side Row Model	❌	✅	❌	✅
Aggregation Footers	❌	✅	✅	✅
Context Menus	❌	✅	✅	✅
Advanced Filtering	Basic	✅	✅	✅
Faceted Search / Token Search	❌	✅	✅	✅
Row Pinning	❌	✅	✅	✅
Master/Detail Rows	❌	✅	❌	✅
Pivot Table	❌	✅	✅	✅
Integrated Charts	❌	✅	✅	✅
Advanced Cell Editors	❌	✅	✅	✅
Excel Export	❌	✅	❌	✅
Formula Engine	❌	❌	❌	✅
Undo / Redo	❌	❌	❌	✅
Range Selection	❌	❌	❌	✅
Clipboard (TSV)	❌	❌	❌	✅
Fill Handle	❌	❌	❌	✅
Transactions	❌	❌	❌	✅
Cell Permissions	❌	❌	❌	✅
Audit Trail	❌	❌	❌	✅
Row Locking	❌	❌	❌	✅
Excel / CSV Import	❌	❌	❌	✅
PDF Export	❌	❌	❌	✅
Filter Presets	❌	❌	❌	✅
Saved Views	❌	❌	❌	✅
Form Editor	❌	❌	❌	✅
Accessibility (WCAG 2.1 AA + VPAT)	Partial	✅	✅	✅
Built-in Themes	1	Multiple	10	10

This doesn't necessarily mean React DataGrid should replace AG Grid in every project. AG Grid remains one of the most mature data grid solutions available and comes with commercial support for organizations that require enterprise SLAs.

However, if your team needs a capable open-source React data grid with features such as grouping, aggregation, virtualization, theming, and rich customization, React DataGrid's MIT-licensed core presents a compelling option.

When requirements expand to advanced workflows, auditing, permissions, transactions, or spreadsheet-style operations, the Enterprise edition provides an upgrade path without requiring you to switch to a different grid component.

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Who Should Use React DataGrid?

React DataGrid isn't trying to be the right data grid for every React project, and that's actually one of its strengths.

I think it's well suited for:

• Internal business dashboards
• Admin panels
• SaaS applications
• CRM and ERP systems
• Financial dashboards
• Analytics platforms
• Inventory management systems
• Applications that need grouping, aggregation, virtualization, rich customization, or Server-Side Infinite Scroll for large datasets without paying for a commercial grid
• Enterprise applications that may need advanced capabilities

If your application starts with a few hundred rows today but could eventually grow into tens of thousands, or even millions, of records, it's nice to know you won't need to replace your grid component later just because your data has outgrown it.

📌 If you find this useful, consider starring the GitHub repo; it helps support the open-source project and its continued development.

⭐ Star React DataGrid on GitHub

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Final Thoughts

What stands out about React DataGrid isn't a single headline feature; it's the combination of an open-source core and an optional Enterprise edition that can grow with an application's requirements.

The MIT-licensed core provides developers with a capable React data grid for everyday data management, including sorting, filtering, grouping, aggregation, virtualization, theming, customization, and accessibility.

For teams that need more advanced workflows, the Enterprise edition adds capabilities such as Server-Side Row Model, Master/Detail, Formula Engine, Transactions, Cell Permissions, Audit Trail, Row Locking, Excel/CSV Import, PDF Export, Filter Presets, Saved Views, and Form Editor.

That gives teams a straightforward choice:

• Start with the free, open-source grid for projects that don't need commercial features
• Move to the Enterprise edition when more advanced data operations and workflows become necessary.

This article focused on what React DataGrid offers and how its free and Enterprise capabilities compare. In my next article, I'll take a different approach by building a real React project with it, sharing the complete development experience, highlighting what worked well, and discussing any challenges I encounter along the way. Stay tuned!

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Thanks for reading! 🙏🏻 I hope you found this useful ✅ Please react and follow for more 😍 Made with 💙 by Hadil Ben Abdallah

Hadil Ben AbdallahFollow

Software Engineer • Technical Writer (300K+ readers & 20K+ followers) • Trusted by 10+ companies I turn brands into websites people 💙 to use

Comments

[Dev Monster]

Great breakdown! This is pretty helpful for me because even though I was using React Data Grid for years, till now I feel lost between libraries and components every time I work on a table, and as you said, the biggest problem is that the most important features most of the free libraries either limit or don't offer at all.
I'm definitely going to give DataGrid a try in my next React project.
Thank you so much!

[Hadil Ben Abdallah]

Thank you so much! I really appreciate that.
And I completely get what you mean. There are so many React grid options out there that choosing the right one can sometimes feel like a project on its own 😅
I’m glad the breakdown helped make things clearer. Definitely give React DataGrid a try on your next project, and I’d love to hear how it goes once you’ve had some hands-on time with it!

[Aida Said]

This article really solves the endless search for a good table library 😂 Hearing that there is a library that has all those features available under the MIT license really made my day 😍

[Hadil Ben Abdallah]

Haha, I can feel you 😅 Finding a table library that checks all the right boxes can turn into an endless hole.
I’m really glad you found the MIT-licensed approach as exciting as I did! Hopefully React DataGrid saves you from a few search times 😍