SVAR UI
AG Grid
DataTables
Handsontable
Grid.js
angular-gantt
Webix Grid
RevoGrid
Plotly
D3.js
RAWGraphs
Tableau
Google Charts
Highcharts
Bokeh
Chart.js
SVAR UI is a collection of high-performance, framework-native UI components for building modern web applications in React, Svelte, and Vue. Each component is built natively for its target framework and ships with full TypeScript support, so you get type safety, autocompletion, and a smooth developer experience from day one. With an MIT-licensed core, rich APIs, and easy CSS-based customization, SVAR lets teams add complex data, scheduling, and task-management interfaces in minutes instead of weeks.
SVAR DataGrid enables developers to create robust, high-performance tables with advanced features like in-cell editing, frozen columns, context menus, multi-column sorting, advanced filtering, and virtualization for large datasets.
SVAR Gantt Chart stands out as a powerful tool for task management and scheduling. Its interactive interface allows users to add and manage tasks with drag-and-drop functionality or intuitive form. Its customizable timelines, rich API and ease of use make it an ideal solution for visualizing project workflows.
SVAR Calendar is a framework-native scheduling component with Day, Week, and Month views, drag-and-drop event management, a built-in event editor, calendar grouping, and filtering.
SVAR Kanban is a drag-and-drop task board component with configurable columns and rich cards that display priority, tags, progress, deadlines, and assignees.
File Manager is a UI component with the familiar file browser's features such as file previews, split/list/thumbnail views, and support for basic file operations like copying, deleting, uploading, and downloading.
SVAR Core is a UI library of essential UI controls, including buttons, date pickers, combo boxes, popups, menus, and toolbar.
With a focus on optimized performance, rich interactivity, and ease of customization, SVAR UI components provide developers with the tools they need to build modern, high-performance web applications.
SVAR UI PlotlyPlotly is recommended for data scientists, analysts, and developers who need to create interactive and visually appealing data visualizations. It's particularly useful for those who work with Python or R and want the ability to embed their visualizations in web applications or dashboards.
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SVAR UI's answer
SVAR UI offers a set of complex, feature-rich UI building blocks, like calendar, Gantt chart, kanban board or data grid. Because SVAR components are framework-native, you avoid the boilerplate, compatibility issues, and performance overhead that come with wrapper-based libraries.
The components are optimized for large datasets and come with production-ready workflows out of the box — drag-and-drop scheduling, in-cell editing, context menus, and built-in editors — so you integrate in minutes instead of building forms and dialogs yourself. CSS-variable-based theming model makes customization straightforward across all three frameworks.
The free MIT-licensed core takes most projects far, the PRO edition covers advanced, enterprise-grade features.
SVAR UI's answer
SVAR UI components are written natively in Svelte, React and Vue, and use CSS for styling.
SVAR UI's answer
Front-end developers and engineering teams building modern web applications in React, Svelte, or Vue who need complex, data-heavy, or scheduling interfaces — data grids, Gantt charts, calendars, Kanban boards, and file managers. SVAR is especially well-suited to teams building project management tools, booking systems, logistics dashboards, and internal business apps who want framework-native components with TypeScript support, strong performance, and a low-config customization model rather than a wrapper library or a heavy all-in-one suite.
SVAR UI's answer
SVAR UI is built as native React, Svelte, and Vue components rather than framework wrappers, so each implementation works directly with its framework's rendering and state patterns. Every component ships with full TypeScript support, a rich API, an MIT-licensed core. Combined with virtualization, CSS-based theming, and localization built in, it delivers complex data, project management, and scheduling interfaces with minimal setup.
SVAR UI's answer
SVAR began with SVAR Svelte Core, an open-source library of form controls and essential UI elements, released in October 2023. Since then, it has grown to include advanced widgets like DataGrid, Gantt, File Manager, Calendar, Kanban, and more. In 2024-2025, React versions of the components were released, and in 2026 SVAR UI was extended with the Vue 3 version of the components. Also, Calendar and Kanban components were released in Svelte, React, and Vue versions.
Based on our record, Plotly seems to be more popular. It has been mentiond 34 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Let's dive into some practical examples. First, you'll need to set up your environment with the right tools. I recommend using pandas for data manipulation and plotly for visualization. - Source: dev.to / 6 months ago
Plotly is perfect for interactive visualizations. You can create interactive charts and graphs that allow users to hover, click, and zoom in. Plotly is also great for web-based visuals, making it easy to share your findings online. - Source: dev.to / over 1 year ago
Front End: A React application that leverages React-Chatbotify library to easily integrate a chatbot GUI. It also uses the Plotly library to display the charts/visualizations. The generative AI implementation and details are entirely abstracted from the front end. The front-end application depends on a single REST endpoint of the backend application. - Source: dev.to / over 1 year ago
In this tutorial, Mariya Sha will guide you through building a stock value dashboard using Taipy, Plotly, and a dataset from Kaggle. - Source: dev.to / almost 2 years ago
How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / about 2 years ago
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