Angular has changed in recent versions, especially around how developers handle reactive state. Signals are now an important part of the framework, and that makes the architecture behind an Angular component worth paying attention to.
Data grids are a good example.
A grid can start as a simple list of rows and columns. Then requirements start piling up: sorting, filtering, editing, large datasets, virtualization, grouping, pivot tables, accessibility, theming, and more. Building all of those capabilities around a basic table can become a project of its own.
That's where Angular DataGrid comes in. It's an open-source, MIT-licensed Angular data grid built with Angular, TypeScript, and Angular CDK, with a Signals-based architecture and a separate paid Enterprise tier for advanced spreadsheet and data-governance features.
In this article, I'll go through what Angular DataGrid offers, how to get started with it, which features matter when you're dealing with large datasets, how its free and Enterprise tiers differ, and how it compares with AG Grid.
TL;DR
Angular DataGrid is a free, MIT-licensed Angular data grid built around modern Angular patterns, including Signals, with Angular CDK powering its virtualization layer. The project currently reports 100k+ rows supported, 25+ built-in features, 116 passing tests, and $0 license cost for the open-source tier.
Here's what Angular DataGrid brings to the free tier:
✅ MIT-licensed open-source core
✅ Signals-based architecture
✅ Virtual scrolling for large datasets
✅ Sorting, filtering, pagination, and quick search
✅ Row selection and inline editing
✅ Column resizing, reordering, pinning, and layout persistence
✅ Row grouping, aggregation, and Tree Data
✅ Basic Master/Detail
✅ Pivot tables and integrated charts
✅ Faceted search and live updates
✅ Context menus, tooltips, overlays, and cell/row styling
✅ Light, dark, and high-contrast themes
✅ Keyboard navigation and ARIA grid semantics
✅ CSV export
✅ No separate CSS import required
There is also an optional Enterprise tier for capabilities such as Formula Engine, Undo/Redo, Range Selection, Fill Handle, Server-Side Row Model, Cell Permissions, Audit Trail, Row Locking, Spreadsheet Import, PDF Export, Saved Views, and Form Editor.
So if you're looking for an Angular data grid that gives you a broad feature set without a commercial license for the core functionality, Angular DataGrid is worth evaluating.
What Are Angular Data Grid Components?
An Angular data grid component is a table-like UI component designed for large, interactive datasets. It typically handles features such as sorting, filtering, pagination, inline editing, row selection, column management, and data visualization as part of the grid itself.
That's different from rendering a normal HTML table with *ngFor.
A basic Angular table can work perfectly well for a small dataset. Once the number of rows grows, though, the browser has to deal with a much larger DOM, and developers have to build more of the interaction layer themselves.
There is no built-in virtualization in a plain table. Sorting, filtering, editing, selection, column resizing, keyboard navigation, and other behaviors also need to be implemented separately.
A data grid brings those concerns into one component.
For applications such as admin dashboards, inventory systems, analytics tools, CRM interfaces, financial applications, and internal data platforms, that can make a big difference in how much grid-specific code the application needs to maintain.
The important distinction is that a data grid isn't simply a prettier table. It's an interactive data-management component designed around the problems that appear when users need to work with a lot of structured information.
What Features Really Matter in an Angular Data Grid?
A long feature list doesn't automatically make a data grid useful.
The features need to solve actual problems that appear when applications start working with structured and growing datasets.
When evaluating an Angular data grid, I'd look at five areas first: performance, data operations, hierarchical data, accessibility, and customization. These are also the areas highlighted in the Angular DataGrid brief.
Performance at Scale
The first thing to consider is how the grid behaves when the number of records grows.
Rendering a few dozen rows is easy. Rendering thousands of rows creates a very different workload for the browser.
That's why virtual scrolling matters.
A virtualized grid can keep the number of DOM elements under control by rendering the portion of the dataset that needs to be visible.
For data-heavy applications, this is one of the first capabilities I'd check.
Data Operations
Users need ways to find, organize, and analyze the records that matter.
That starts with sorting and filtering, but production applications often need more.
Multi-column sorting, text/number/date/set filters, quick-filter search, row grouping, aggregation, and pivoting can turn a large dataset into something users can actually explore.
The difference becomes obvious when a grid contains thousands of records. A user shouldn't have to scroll through the entire dataset to answer something as simple as:
- Which records match this condition?
- Which items have the highest value?
- How are records distributed across categories?
- What does the data look like when grouped by a particular field?
A capable grid should handle those interactions as part of its data-management layer.
Hierarchical Data
Not every dataset is flat.
Organizations have departments and employees. Projects have tasks and subtasks. Products have categories and variants. Applications can also contain parent records with additional detail.
Here, Tree Data and Master/Detail become useful.
Tree Data lets users expand and collapse hierarchical records, while Master/Detail can expose additional information associated with a row.
Accessibility
Accessibility is easy to overlook when evaluating data grids.
A production grid needs more than clickable cells. Keyboard navigation, focus management, and correct ARIA semantics all matter when users need to operate the grid without relying entirely on a mouse.
Customization
Finally, the grid needs to look and behave like part of the application.
A data grid might need a light theme in one product and a dark theme in another. Some applications also need compact density, custom cell renderers, conditional row styling, tooltips, overlays, or application-specific colors.
Introducing Angular DataGrid
Angular DataGrid is a Signals-based Angular open-source data grid built with Angular, TypeScript, and Angular CDK. It's distributed through the @gridengine/angular-datagrid npm package and released under the MIT license.
The Signals-based architecture is an important part of how the project is designed. This isn't just an Angular wrapper around a generic grid component. Angular DataGrid is built as an Angular component with Signals at its core.
The project homepage currently lists:
- 100k+ rows supported
- 25+ built-in features
- 116 passing tests
- $0 license cost for the open-source tier
The project follows the existing react-open-source-datagrid project as its reference specification, but the Angular version is built around Angular's Signals-based architecture.
Angular DataGrid is part of the broader GridEngine platform, which provides data grid solutions for different technologies and use cases.
Installation & Quick Start
Getting Angular DataGrid into an Angular project is straightforward.
Install the grid package together with its Angular CDK peer dependency:
npm install @gridengine/angular-datagrid @angular/cdk
The basic component API lets you provide row data and column definitions directly from an Angular component.
A minimal example looks like this:
import { Component } from '@angular/core';
import { DataGrid, ColDef } from '@gridengine/angular-datagrid';
@Component({
selector: 'app-team',
imports: [DataGrid],
template: `<gd-data-grid [rowData]="rowData" [columnDefs]="columnDefs" />`,
})
export class TeamComponent {
rowData = [
{ id: 1, name: 'Ada Lovelace', role: 'Engineer' },
{ id: 2, name: 'Grace Hopper', role: 'Engineer' },
];
columnDefs: ColDef[] = [
{ field: 'id', headerName: 'ID', width: 80 },
{ field: 'name', headerName: 'Name', sortable: true },
];
}
One small detail is worth calling out:
There is no separate CSS file to import.
Angular DataGrid ships its styles inside the component through Angular view encapsulation. Themes and density can be configured through component inputs or --gd-* CSS custom properties.
That keeps the initial setup clean: install the package, import the component, provide the rows and columns, and then start configuring the features your application needs.
The basic grid is only the starting point. The library's feature set covers everyday data operations, large-scale rendering, grouping and hierarchy, real-time data, search, visualization, accessibility, and customization.
Core Features Walkthrough
The basic setup gets a grid on the screen, but the real value of a data grid comes from everything users can do once the data is there.
Angular DataGrid's feature set covers the everyday interactions you'd expect from a modern grid, along with grouping, hierarchical data, analytics, search, real-time updates, visualization, accessibility, and UI customization. It lists 25+ built-in features across these areas.
Let's break those capabilities down by the problems they solve.
Everyday Grid Interactions
For a typical admin dashboard or data-management screen, users need to manipulate the grid without writing custom UI around every operation.
Angular DataGrid includes multi-column sorting, several filter types, pagination, quick-filter search, checkbox-based row selection, and inline editing.
The available everyday interactions include:
- Multi-column sorting
- Text filters
- Number filters
- Date filters
- Set filters
- Quick-filter search
- Pagination
- Checkbox row selection
- Inline editing
- Text, number, date, select, and checkbox editors
This gives users several ways to move through a large dataset.
For example, someone managing customer records could sort by account value, filter by status, select several rows, and update a field directly inside the grid.
That workflow becomes even more useful when the grid is being used as the main workspace of an application.
Virtual Scrolling for Large Datasets
Performance becomes a bigger concern as the number of records increases.
Angular DataGrid uses virtual scrolling to keep the rendered portion of the grid manageable.
Users can work with a large dataset while the browser only needs to render the rows currently relevant to the viewport.
The project supports 100,000+ rows, with Angular CDK-backed virtualization listed as part of the implementation.
Consider a grid containing 50,000 records.
A conventional table would create a very large DOM if all of those records were rendered at once. A virtualized grid can keep the visible portion small while the user scrolls through the larger collection.
For Angular applications dealing with large administrative datasets, analytics records, inventory, or operational data, this is one of the features worth testing early.
Sorting, Filtering, and Quick Search
Sorting and filtering are simple features until the dataset becomes large enough that users depend on them for almost every interaction.
Angular DataGrid supports multi-column sorting along with text, number, date, and set filters. There's also a quick-filter search bar for rapidly narrowing the records displayed by the grid.
That combination gives users both precise and fast ways to find information.
For example, a support dashboard could filter tickets by status, search for a customer name, and then sort the remaining records by priority and creation date.
The important part is that these operations are already part of the grid's feature set. Developers don't have to construct a separate filtering interface for every dataset.
Selection and Inline Editing
Data grids often become more useful when users can work with records directly.
Angular DataGrid supports checkbox-based row selection and inline editing with several editor types:
- Text
- Number
- Date
- Select
- Checkbox
That covers a wide range of common CRUD-style interfaces.
A product-management grid, for example, could allow a user to select records for a batch workflow while also editing a product's name, price, category, or availability directly inside the relevant cells.
This keeps routine changes close to the data being managed.
Column Operations, Pinning, and Layout Persistence
Users don't always want to view a grid in the same way.
Angular DataGrid includes column resizing, column reordering, left and right column pinning, and layout persistence.
Column pinning is useful when important information needs to remain visible while the user moves horizontally through a wide dataset.
Layout persistence adds another practical layer. A user can arrange the columns around their workflow and have that preferred layout restored later.
These features can become important when a grid has many columns and different users need different views of the same underlying data.
Row Pinning, Dragging, and Cell/Row Styling
The grid also includes UI features for controlling how important records are presented.
Row pinning can keep selected rows at the top or bottom of the grid, while drag-and-drop interactions support row reordering workflows.
Angular DataGrid also supports cell and row styling, giving developers control over how specific data should appear. The feature list groups these capabilities with the grid's broader visualization and UI features.
That can be useful for conditional interfaces where a row needs to communicate something visually, such as a warning state, status, priority, or other application-specific condition.
Tooltips, Overlays, and Context Menus
A dense data grid can contain a lot of information in a small amount of screen space.
Angular DataGrid includes tooltips and overlays for displaying supporting information without permanently adding more content to every row or cell.
It also includes a context menu with actions such as copying data and exporting CSV.
This gives users another interaction layer when working with records, especially in interfaces where right-click or contextual actions make sense.
Grouping, Hierarchy, and Data Analysis
Once a dataset becomes more complex, a flat list of rows can make relationships difficult to understand.
Angular DataGrid addresses this with several features for grouping, hierarchy, and analysis.
Row Grouping and Aggregation
Row grouping lets users organize records according to shared values.
For example, an employee dataset could be grouped by department, while an order dataset could be grouped by customer or region.
Grouping becomes more useful when combined with aggregation, because users can work with summarized values alongside the individual records.
This changes the grid from a simple record viewer into a tool for exploring how a dataset is structured.
Tree Data
Some datasets naturally have parent-child relationships.
Angular DataGrid's Tree Data support lets users expand and collapse hierarchical records.
Think about a project management application.
A project could contain phases, each phase could contain tasks, and tasks could have nested subtasks. A flat table would make that hierarchy harder to follow. Tree Data gives users an expandable structure that reflects the underlying relationships.
The same approach can work for organizational structures, file systems, product categories, or other nested datasets.
Master/Detail
Master/Detail provides another way to expose related information.
The free tier includes basic expandable Master/Detail panels, allowing users to open additional information associated with a row.
This can be useful when the main grid needs to stay compact while each record has additional fields or related data that users only need occasionally.
The Enterprise tier later extends this concept with advanced Master/Detail, including lazy-loaded and cached detail rows for larger nested datasets.
Pivot Tables
A Pivot Table is useful when users need to look at the same dataset from different dimensions.
For example, sales data could be organized by region across columns and product categories across rows, allowing users to inspect totals from a different perspective.
Angular DataGrid includes Pivot Table functionality in its free tier.
That is a meaningful capability for analytics-heavy applications because pivoting can answer questions that are difficult to explore through a conventional row-by-row grid.
Integrated Charts
Angular DataGrid also includes Integrated Charts, which can generate quick SVG charts from grid selections.
The useful part here is the connection between the grid and the visualization.
A user can work with a subset of the data, select what they want to analyze, and turn that selection into a visual representation.
For internal analytics tools and dashboards, this can reduce the need to create a separate visualization flow for every small data-exploration task.
Faceted Search and Live Data
Some applications deal with datasets that change continuously.
Monitoring dashboards, operational systems, financial interfaces, and real-time analytics applications all need ways to make those changes visible.
Angular DataGrid includes two features aimed at this kind of workflow: faceted search and live updates.
Faceted Search
Faceted search combines filtering with information about the values available in the dataset.
Angular DataGrid's feature list describes it as supporting value counts and token search.
That can help users understand the dataset while narrowing it down.
For example, if a status field contains several possible values, seeing the available values and their counts gives users more context when deciding which filters to apply.
Live Updates
For changing datasets, Angular DataGrid can provide live updates with flash-on-change cells.
When a value changes, the cell can visually indicate that an update occurred.
That small interaction can make a big difference in monitoring interfaces. Users don't have to repeatedly scan every value to figure out what changed.
Theming and Customization
A data grid usually needs to match the rest of the application.
Angular DataGrid includes light, dark, and high-contrast themes, along with density modes and CSS custom-property overrides. It also supports custom cell renderer templates.
For example:
<gd-data-grid
[rowData]="rowData"
[columnDefs]="columnDefs"
theme="dark"
density="compact"
/>
<style>
gd-data-grid {
--gd-accent-color: #7c3aed;
--gd-border-color: #334155;
}
</style>
The CSS custom properties make it possible to adjust the visual details of the grid while keeping the component inside Angular's view-encapsulation model.
Custom cell renderers are useful when a standard text value isn't enough.
A status column could display badges. A score column could use a visual indicator. A date column could use application-specific formatting.
That gives developers more control over the final UI without having to replace the grid's underlying rendering system.
Accessibility and Keyboard Navigation
Accessibility deserves its own mention because data grids can become difficult to operate when keyboard and focus behavior are handled poorly.
Angular DataGrid includes roving-tabindex keyboard navigation and ARIA grid semantics.
The goal is to make the grid's interactive structure understandable to assistive technologies while giving keyboard users a predictable way to move through the interface.
For applications used by a broad range of users, these details are part of the grid's overall quality, not an optional visual enhancement.
Documentation and Grid API
Angular DataGrid also exposes an imperative Grid API, alongside API documentation covering inputs, outputs, methods, and ColDef.
This matters when the declarative component configuration isn't enough for a more complex application.
A grid may need to react to an external event, trigger an operation programmatically, or coordinate its state with another part of the application.
Having an API layer gives developers a way to integrate those interactions into a larger Angular application.
Free vs. Enterprise: What's Actually Free?
At this point, it's important to separate the open-source functionality from the paid Enterprise features.
The free Angular DataGrid tier is MIT-licensed and includes a much broader set of functionality than basic sorting and pagination. That includes virtual scrolling, sorting and filtering, selection, editing, column operations, grouping and aggregation, Tree Data, basic Master/Detail, Pivot Table, faceted search, live updates, integrated charts, context menus, styling, theming, accessibility, and CSV export.
The project also has a separate Enterprise tier for teams that need more advanced spreadsheet workflows, backend-driven data handling, collaboration controls, and governance features.
The Enterprise feature list includes:
- Formula Engine: Excel-style formulas evaluated directly in cells
- Undo / Redo: Multi-step edit history
- Range Selection: Excel-style cell-range selection
- Clipboard (TSV): Excel-compatible copy and paste
- Fill Handle: Drag-to-fill series and copy operations
- Advanced Master/Detail: Lazy-loaded and cached detail rows
- Server-Side Row Model: Block-fetched data for huge backend-driven datasets
- Transactions: Staged add, update, and remove operations
- Cell Permissions: Per-cell read/edit controls
- Audit Trail: Immutable edit history
- Row Locking: Collaborative row locks
- Excel / CSV Import: Mapping, validation, and coercion of spreadsheet data
- PDF Export: Branded, paginated PDF documents
- Filter Presets: Savable AND/OR filter configurations
- Saved Views: Personal and shared grid layouts
- Form Editor: Slide-in panel for structured record editing
These Enterprise capabilities are explicitly separated from the free feature set in the project brief.
Here's the distinction at a glance:
| Category | Free / Open-Source | Enterprise |
|---|---|---|
| License | MIT | Paid |
| Virtual Scrolling | ✅ | ✅ |
| Sorting & Filtering | ✅ | ✅ |
| Pagination | ✅ | ✅ |
| Quick Filter | ✅ | ✅ |
| Row Selection | ✅ | ✅ |
| Inline Editing | ✅ | ✅ |
| Column Resize / Reorder | ✅ | ✅ |
| Column Pinning | ✅ | ✅ |
| Layout Persistence | ✅ | ✅ |
| Row Pinning & Drag | ✅ | ✅ |
| Row Grouping & Aggregation | ✅ | ✅ |
| Tree Data | ✅ | ✅ |
| Master/Detail | Basic | Advanced |
| Pivot Table | ✅ | ✅ |
| Faceted Search | ✅ | ✅ |
| Live Updates | ✅ | ✅ |
| Integrated Charts | ✅ | ✅ |
| Context Menu | ✅ | ✅ |
| Cell & Row Styling | ✅ | ✅ |
| Tooltips & Overlays | ✅ | ✅ |
| Theming & Density | ✅ | ✅ |
| Keyboard Navigation & ARIA | ✅ | ✅ |
| CSV Export | ✅ | ✅ |
| Formula Engine | ❌ | ✅ |
| Undo / Redo | ❌ | ✅ |
| Range Selection | ❌ | ✅ |
| Clipboard (TSV) | ❌ | ✅ |
| Fill Handle | ❌ | ✅ |
| Server-Side Row Model | ❌ | ✅ |
| Transactions | ❌ | ✅ |
| Cell Permissions | ❌ | ✅ |
| Audit Trail | ❌ | ✅ |
| Row Locking | ❌ | ✅ |
| Excel / CSV Import | ❌ | ✅ |
| PDF Export | ❌ | ✅ |
| Filter Presets | ❌ | ✅ |
| Saved Views | ❌ | ✅ |
| Form Editor | ❌ | ✅ |
The split makes the positioning fairly clear. A team can use the MIT-licensed core for a broad range of data-heavy Angular applications, then consider Enterprise when the requirements move toward spreadsheet-style editing, backend-driven datasets, collaborative controls, or stronger governance.
That licensing distinction also becomes important when comparing Angular DataGrid with AG Grid, because several advanced capabilities available in Angular DataGrid's free tier are associated with AG Grid Enterprise.
How Angular DataGrid Compares to AG Grid
If you're searching for an AG Grid alternative for Angular, the important comparison is not just the total number of features. It's how much functionality you get in the free tier.
AG Grid Community is free and open source, while features such as row grouping, pivoting, Tree Data, Master/Detail, Server-Side Row Model, Integrated Charts, and Enterprise context-menu functionality are part of AG Grid Enterprise.
Angular DataGrid takes a different approach with its free MIT-licensed tier.
Here's a broader comparison between AG Grid and Angular DataGrid:
| Feature | AG Grid Community | AG Grid Enterprise | Angular DataGrid Free | Angular DataGrid Enterprise |
|---|---|---|---|---|
| License | MIT | Commercial | MIT | Paid |
| Virtual Scrolling | ✅ | ✅ | ✅ | ✅ |
| Sorting | ✅ | ✅ | ✅ | ✅ |
| Multi-Column Sorting | ✅ | ✅ | ✅ | ✅ |
| Filtering | ✅ | ✅ | ✅ | ✅ |
| Text / Number / Date Filters | ✅ | ✅ | ✅ | ✅ |
| Set Filter | ❌ | ✅ | ✅ | ✅ |
| Quick Filter | ✅ | ✅ | ✅ | ✅ |
| Pagination | ✅ | ✅ | ✅ | ✅ |
| Checkbox Row Selection | ✅ | ✅ | ✅ | ✅ |
| Inline Editing | ✅ | ✅ | ✅ | ✅ |
| Text / Number / Date / Select / Checkbox Editors | ✅ | ✅ | ✅ | ✅ |
| Column Resizing | ✅ | ✅ | ✅ | ✅ |
| Column Reordering | ✅ | ✅ | ✅ | ✅ |
| Column Pinning | ✅ | ✅ | ✅ | ✅ |
| Layout Persistence | ✅ | ✅ | ✅ | ✅ |
| Row Pinning | ✅ | ✅ | ✅ | ✅ |
| Row Dragging | ✅ | ✅ | ✅ | ✅ |
| Row Grouping | ❌ | ✅ | ✅ | ✅ |
| Aggregation | ❌ | ✅ | ✅ | ✅ |
| Tree Data | ❌ | ✅ | ✅ | ✅ |
| Master/Detail | ❌ | ✅ | Basic | Advanced |
| Pivot Table | ❌ | ✅ | ✅ | ✅ |
| Context Menu | ❌ | ✅ | ✅ | ✅ |
| Integrated Charts | ❌ | ✅ | ✅ | ✅ |
| Faceted Search | ❌ | ❌ | ✅ | ✅ |
| Live / Flash Updates | ❌ | ❌ | ✅ | ✅ |
| Cell & Row Styling | ✅ | ✅ | ✅ | ✅ |
| Tooltips & Overlays | ✅ | ✅ | ✅ | ✅ |
| Theming | ✅ | ✅ | ✅ | ✅ |
| Density Modes | ✅ | ✅ | ✅ | ✅ |
| Custom Cell Renderers | ✅ | ✅ | ✅ | ✅ |
| Keyboard Navigation | ✅ | ✅ | ✅ | ✅ |
| ARIA Grid Semantics | ✅ | ✅ | ✅ | ✅ |
| CSV Export | ✅ | ✅ | ✅ | ✅ |
| Formula Engine | ❌ | ✅ | ❌ | ✅ |
| Undo / Redo | ❌ | ✅ | ❌ | ✅ |
| Range Selection | ❌ | ✅ | ❌ | ✅ |
| Clipboard (TSV) | ❌ | ✅ | ❌ | ✅ |
| Fill Handle | ❌ | ✅ | ❌ | ✅ |
| Advanced Master/Detail | ❌ | ✅ | ❌ | ✅ |
| Server-Side Row Model | ❌ | ✅ | ❌ | ✅ |
| Transactions | ❌ | ✅ | ❌ | ✅ |
| Cell Permissions | ❌ | ❌ | ❌ | ✅ |
| Audit Trail | ❌ | ❌ | ❌ | ✅ |
| Row Locking | ❌ | ❌ | ❌ | ✅ |
| Excel / CSV Import | ❌ | ✅ | ❌ | ✅ |
| PDF Export | ❌ | ✅ | ❌ | ✅ |
| Filter Presets | ❌ | ✅ | ❌ | ✅ |
| Saved Views | ❌ | ❌ | ❌ | ✅ |
| Form Editor | ❌ | ❌ | ❌ | ✅ |
Who Should Use Angular DataGrid?
Angular DataGrid makes sense for Angular teams that need a serious data grid without immediately committing to a commercial grid license.
I'd consider it a good fit for:
- Internal admin tools where users manage large collections of records
- SaaS dashboards that need sorting, filtering, grouping, and interactive exploration
- Analytics applications that benefit from Pivot Tables and Integrated Charts
- Data-heavy Angular applications where virtual scrolling becomes important
- Applications with hierarchical data that can use Tree Data or Master/Detail
- Custom Angular interfaces that need control over themes, density, and cell rendering
- Teams evaluating an AG Grid alternative that want advanced functionality in the free tier
If your application needs spreadsheet-grade collaboration or governance from day one, features such as Undo/Redo, Range Selection, Cell Permissions, Audit Trail, Row Locking, or Server-Side Row Model belong to the Enterprise tier.
That makes the licensing model worth considering early. The free tier covers a broad range of standard data-grid requirements, while Enterprise gives teams a path forward when the application needs more advanced workflows.
📌 If you find this useful, consider starring the GitHub repo; it helps support the open-source project and its continued development.
⭐ Star Angular DataGrid on GitHub
Frequently Asked Questions
What is an Angular data grid?
→ An Angular data grid is an interactive table component designed for working with structured datasets. It typically provides features such as sorting, filtering, selection, editing, column management, virtualization, and data analysis without requiring developers to build each interaction around a basic HTML table.
What features should I look for in an Angular data grid?
→ The most useful features depend on the application, but large Angular applications commonly need virtualization, sorting, filtering, inline editing, row selection, column management, grouping, hierarchical data, accessibility, and theming. Analytics-heavy applications may also need pivot tables and integrated charts.
Is Angular DataGrid free to use?
→ Yes. Angular DataGrid's core is MIT-licensed and free, including virtual scrolling, grouping, Tree Data, Pivot Tables, Integrated Charts, theming, accessibility, and other core grid features. A separate Enterprise tier adds capabilities such as formulas, Undo/Redo, range selection, server-side data handling, and governance features.
Does Angular DataGrid support Angular Signals?
→ Yes. Angular DataGrid is built as a Signals-based Angular component, making Signals part of its underlying architecture.
Do I need to import a separate CSS file for Angular DataGrid?
→ No. The library ships its styles inside the component through Angular view encapsulation, so there is no separate CSS file to import. Themes and density can be configured through component inputs and --gd-* CSS custom properties.
Final Thoughts
Angular DataGrid gives Angular developers a broad MIT-licensed feature set that goes well beyond basic table functionality.
Virtual scrolling, grouping, Tree Data, Pivot Tables, Integrated Charts, theming, accessibility, and live updates are available in the free tier, while Enterprise adds a clear path for more advanced spreadsheet and governance requirements.
For Angular teams evaluating data grids, the main point is simple. You don't have to start with a commercial license to get a feature-rich grid, and you still have an Enterprise path when your application's requirements grow.
| Thanks for reading! 🙏🏻 I hope you found this useful ✅ Please react and follow for more 😍 Made with 💙 by Hadil Ben Abdallah |
  
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Top comments (2)
Anyone who has had to deal with AG Grid’s enterprise licensing costs knows how needed a solid MIT-licensed alternative is. Really like that this is built natively around Angular Signals rather than just being an awkward wrapper.
A library with this amount of MIT-licensed features is really amazing. I'm ganna try it in my next project.