12 repositorios
Frontend components that use virtualization to efficiently display large datasets or complex traces.
Distinguishing note: Focuses on UI performance for large data sets rather than general-purpose UI components.
Explore 12 awesome GitHub repositories matching user interface & experience · Virtualized Data Rendering. Refine with filters or upvote what's useful.
Element Plus is a Vue.js UI component library and enterprise web design system used for building professional web applications with Vue.js 3. It provides a comprehensive set of pre-styled interactive components and tools designed for creating responsive user interfaces. The project includes a customizable component theme system for managing global CSS variables and dark mode palettes. It also features a Vue.js migration toolkit with automated transpilation tools to convert legacy UI code to current component standards. The library covers a wide range of capability areas, including high-perfo
Implements high-performance data tables with virtual scrolling and complex filtering for large datasets.
SigNoz is a full-stack observability platform designed to collect, store, and visualize metrics, logs, and distributed traces in a unified environment. It leverages OpenTelemetry-based data collection to ingest telemetry from diverse sources using vendor-neutral protocols, ensuring interoperability across complex microservices architectures. The platform utilizes a high-performance columnar storage engine to enable rapid aggregation and filtering, providing a centralized backend for monitoring application health and performance. What distinguishes the platform is its focus on automated instru
Uses progressive loading and virtualized lists to display complex distributed traces containing millions of spans efficiently.
Plotly.py is a comprehensive framework for building production-ready data applications and interactive dashboards directly from Python code. It functions as both a high-performance visualization library for browser-based charts and a full-stack tool for transforming analytical scripts into responsive, web-based interfaces. By abstracting away the need for manual HTML or JavaScript, it allows developers to define complex layouts and functional logic using modular, reusable components. The framework distinguishes itself through a robust architecture that handles event orchestration and state sy
Renders massive and intricate data structures as interactive, real-time graphs to facilitate deeper analysis.
React-window is a frontend performance optimization library designed to render large datasets in React applications. It implements virtualization techniques to manage long lists and complex tabular data by dynamically mounting and unmounting elements based on the current viewport. By limiting the number of active document nodes, the library maintains interface responsiveness when handling thousands of data entries. The library distinguishes itself through a focus on efficient layout calculations and scroll-driven reconciliation. It uses absolute positioning and predefined dimensions to determ
Renders only visible grid cells to maintain high performance when displaying large tabular datasets.
ApexCharts is a comprehensive JavaScript charting library designed for building interactive, responsive, and data-driven visualizations within web applications. It functions as a versatile data visualization framework that supports a wide range of chart types, including categorical, statistical, and financial plots, enabling developers to construct complex dashboards and real-time monitoring interfaces. The library distinguishes itself through a deep commitment to accessibility and high-performance interactivity. It provides built-in support for keyboard navigation, screen readers, and high-c
Uses virtualized rendering to maintain high performance when displaying massive datasets.
gpui-component is a native desktop UI kit and component library built for the GPUI framework. It provides a collection of reusable user interface elements, a desktop layout engine for organizing application space, and a specialized data visualization library for rendering quantitative information. The project is distinguished by its high-performance rendering systems, including a virtualized data grid and list system designed to handle large datasets with low memory overhead. It also features a comprehensive data visualization toolkit for rendering charts, axes, and coordinate scales using li
Ships a high-performance table and list system that uses virtualization to handle large datasets.
Perspective is a columnar data analytics engine and high-performance visualization component powered by WebAssembly. It provides a system for analyzing and visualizing large or streaming datasets through interactive data grids and charts, utilizing a compiled binary to achieve near-native performance within the browser. The project distinguishes itself through a WebSocket-based data streaming interface and deep Apache Arrow integration, which minimize memory overhead when synchronizing tables between servers and clients. It acts as a remote query proxy capable of translating visualization con
Streams only the data required for the current view to efficiently render massive datasets without crashing the browser.
This repository is a comprehensive collection of reference implementations and sample libraries for the Universal Windows Platform. It provides practical examples of how to use Windows Runtime APIs to build cross-device applications, including detailed guidance on XAML-based declarative user interfaces and DirectX-integrated rendering. The project distinguishes itself by providing a wide array of hardware integration suites, covering low-level communication with USB, Serial, I2C, SPI, and GPIO peripherals. It includes specialized implementations for mixed reality holographic rendering, advanc
Implements virtualization to efficiently display large datasets by loading only the visible subset into memory.
vxe-table is a high-performance data table component and UI library for Vue, designed for building data-heavy applications. It functions as a virtualized data grid and spreadsheet UI framework capable of rendering millions of rows by mounting only the visible elements of a dataset. The project distinguishes itself through spreadsheet-like functionality, including cell selection, copy-paste support, and the generation of cross-tabulated pivot tables. It also provides specialized tools for managing complex data hierarchies using virtual trees, row grouping, and cell merging. The library covers
Uses virtualization to efficiently display millions of rows while maintaining high performance during navigation.
Clusterize.js is a vanilla JavaScript virtual list library and DOM virtualization tool. It enables the display of massive data sets by rendering only the subset of rows currently visible within the user viewport. The plugin operates as a lightweight frontend component without external dependencies or framework requirements. It reduces browser memory usage and DOM load by swapping the content of existing elements rather than rendering thousands of nodes simultaneously. The library focuses on frontend performance optimization and large dataset visualization. It maintains a native scrolling exp
Provides highly efficient rendering of massive datasets by only displaying the rows currently visible in the viewport.
Este proyecto es una biblioteca de componentes Blazor y framework de UI web utilizado para construir aplicaciones web con ASP.NET Core Blazor. Sirve como una implementación del Fluent Design System, proporcionando una colección de elementos de interfaz de usuario reutilizables y pre-estilizados para garantizar la consistencia visual y la accesibilidad. La biblioteca incluye una rejilla de datos asíncrona capaz de resolver consultas remotas mediante la obtención de datos asíncrona y mapeo de entidades. Utiliza un sistema de tokens de diseño para gestionar estilos visuales y configuraciones de personalización en toda la aplicación. El framework cubre capacidades más amplias para el diseño de UI empresarial, incluyendo la integración de conjuntos estandarizados de iconos y emojis, y herramientas para componer interfaces accesibles. También proporciona mecanismos para probar la salida de los componentes y verificar el comportamiento del HTML.
Implements a data grid that uses virtualization to efficiently render large datasets by requesting only visible rows.
Este proyecto es un componente de cuadrícula de datos de alto rendimiento diseñado para aplicaciones React. Proporciona un framework declarativo para renderizar conjuntos de datos a gran escala y estructuras tabulares complejas mediante el uso de un motor de dibujo basado en canvas en lugar de nodos tradicionales del DOM. La librería se distingue por un motor de virtualización con ventanas que mantiene un uso constante de memoria al renderizar solo la parte visible de la cuadrícula. Traduce las interacciones del puntero en referencias de celda específicas mediante un mapeo basado en coordenadas y admite la inyección de estado y temas de aplicaciones externas directamente en el entorno de canvas para garantizar un acceso constante a los datos en renderizadores de celdas personalizados. La cuadrícula admite configuraciones de diseño sofisticadas, incluidas filas y columnas fijas, celdas combinadas y encabezados redimensionables. También proporciona herramientas para organizar la información en estructuras jerárquicas basadas en árboles para representar relaciones de datos anidadas. La librería se distribuye como un conjunto de primitivas de React que se integran en aplicaciones web existentes para gestionar el estado de desplazamiento y la reconciliación de diseño para interfaces de datos complejas.
Maintains high performance with massive datasets by rendering only the visible portion of the grid during scrolling.