21 Repos
Renders large datasets at high frame rates with support for interactive zooming.
Distinct from Data Visualization Charts: Distinct from Data Visualization Charts: focuses on performance-optimized rendering for large-scale datasets.
Explore 21 awesome GitHub repositories matching data & databases · High-Performance Visualizers. Refine with filters or upvote what's useful.
Handsontable is a JavaScript data grid that provides a spreadsheet-like interface for managing and editing large datasets within web applications. It functions as a virtualized data table that renders only visible cells to maintain performance, paired with a synchronization layer that binds the grid to underlying data structures. The project distinguishes itself through a built-in spreadsheet calculation engine for evaluating mathematical and logical expressions and a dedicated tool for exporting grid content into Excel XLSX files. It ensures interoperability with external spreadsheet softwar
Displays and scrolls through thousands of rows and columns using virtualization to maintain high browser performance.
Bokeh is a Python data visualization library and interactive plotting framework used to create high-performance graphics and data dashboards that render in web browsers. It serves as a tool for generating standalone HTML documents, embedded components for digital notebooks, and full-stack web applications powered by a Python backend. The project distinguishes itself through its ability to handle large or streaming datasets while maintaining smooth interactivity. It enables linked brushing across multiple views, allowing data selected in one plot to automatically highlight corresponding data i
Maintains high performance when rendering large or streaming datasets using optimized web graphics.
Plotly.js is a JavaScript charting library and interactive graphing framework used to create web-based visualizations. It functions as a high-performance data visualization engine that utilizes both SVG for static elements and WebGL for hardware-accelerated rendering of large datasets and complex 3D plots. The library is distinguished by specialized toolkits for financial analysis, such as candlestick and OHLC charts, and geographic mapping tools for rendering choropleth and scatter maps with custom projections. It also supports complex scientific visualizations, including Sankey diagrams, pa
Utilizes a high-performance WebGL engine for plotting large datasets and complex 3D visualizations in the browser.
DearPyGui is a GPU-accelerated, immediate-mode graphical user interface framework for Python. It provides a high-performance toolkit for building interactive desktop applications by leveraging native hardware-accelerated rendering backends across multiple operating systems. By utilizing an immediate-mode execution model, the library offers direct control over the rendering loop and element state, enabling the creation of responsive, dynamic interfaces. The framework distinguishes itself through its ability to handle complex, high-frequency visual updates, making it suitable for real-time data
Renders high-performance charts capable of displaying over one million data points at sixty frames per second.
deck.gl is a GPU-accelerated geospatial engine and WebGL2 data visualization framework. It functions as a high-performance spatial visualizer and map overlay library designed to render large-scale spatial and temporal datasets. The system specializes in mapping data arrays into visual layers for complex geographic representations. It provides the capability to create interactive visual overlays and cartographic projections that align with various third-party map providers. The framework supports large-scale data visualization, interactive spatial analysis, and the development of custom high-
Provides a high-performance rendering system utilizing GPU acceleration to visualize massive datasets while maintaining responsiveness.
Nivo is a responsive charting framework and a React data visualization library that uses D3 for its underlying math logic. It serves as both a collection of interactive chart components for web applications and a server-side visualization engine for generating static data chart images. The project distinguishes itself by providing a containerized chart rendering API, allowing the visualization engine to be deployed via Docker to serve rendered graphics as images or files through a programmatic interface. It also features a motion engine for animated data transitions, ensuring smooth visual sh
Uses canvas-based rendering to handle thousands of data points with high performance.
sigma.js is a JavaScript graph visualization library and WebGL network renderer designed for drawing large-scale network graphs in web browsers. It functions as a high-performance engine capable of rendering network structures containing thousands of nodes and edges interactively. The library provides a customizable graph engine that allows for the creation of specialized visualizations using low-level graphics primitives and custom drawing layers. It supports the rendering of diverse node shapes, such as images or piecharts, and enables the integration of graph visualizations as overlays on
Offers a high-performance rendering pipeline capable of visualizing network structures with thousands of interactive elements.
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
Employs high-performance virtualized rendering to display large datasets while maintaining interface responsiveness.
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
Implements a high-performance WebAssembly-powered UI component for rendering interactive data grids and charts for large-scale datasets.
uPlot ist eine hochperformante Canvas-Bibliothek für Zeitreihen-Charts, die darauf ausgelegt ist, Millionen von Datenpunkten mit hohen Frameraten zu rendern. Sie fungiert als hochfrequenter Datenvisualisierer und Plotter für Echtzeit-Datenströme und nutzt die HTML5-Canvas-API, um die Responsivität beim Plotten großer zeitlicher Datensätze beizubehalten. Das Projekt zeichnet sich als Plugin-basiertes Visualisierungs-Framework aus, das benutzerdefinierte Renderer erlaubt, um spezialisierte Visuals wie Heatmaps und Box-and-Whisker-Plots zu erstellen. Es dient zudem als interaktives Finanz-Charting-Tool, das speziell OHLC-Charts, Balken und Flächenbänder unterstützt. Die Bibliothek deckt ein breites Spektrum an Funktionen ab, einschließlich Achsenmanagement mit linearen, logarithmischen und uniformen Skalen sowie interaktiver Navigation via Zoomen, Pannen und synchronisierten Cursorn über mehrere verknüpfte Ansichten hinweg. Sie bietet Systeme für dynamisches Daten-Streaming mit Sliding-Window-Buffering und Tools für das Management fehlender Daten sowie zeitzonenbewusste Verarbeitung. Zusätzliche Funktionalität umfasst Stacked-Chart-Aggregation und die Möglichkeit, Visualisierungen in statische Bildformate zu exportieren.
Renders millions of data points at high frame rates using a performance-optimized canvas engine.
react-data-grid is a high-performance table component for React designed to render large datasets using virtualization. It functions as a virtualizing data table that optimizes memory and performance by rendering only the rows and columns currently visible on the screen. The project provides a customizable spreadsheet interface featuring cell editing, column resizing, and pinned rows. It also acts as a hierarchical data grid, supporting row grouping and tree structures to organize complex nested information. The grid covers wide-ranging data management and display capabilities, including mul
Employs high-performance rendering and virtualization to smoothly display massive datasets within a web interface.
ScottPlot is a cross-platform, high-performance charting library for .NET that renders interactive plots across desktop and web GUI frameworks including Windows Forms, WPF, MAUI, Avalonia, Blazor, and WinUI. It provides an optimized rendering engine capable of displaying millions of data points with interactive pan, zoom, and live data streaming, while also supporting image export to formats like PNG and SVG for file output, cloud applications, and notebooks. The library distinguishes itself through a comprehensive set of chart types including scatter, line, bar, pie, heatmap, financial, rada
Renders millions of data points with interactive pan, zoom, and live data streaming.
MapCN is a React component library that wraps MapLibre GL into declarative, composable building blocks for interactive maps. It provides a set of small, reusable components for rendering maps, placing markers, drawing routes, and clustering points, all managed through React hooks, context, and refs for state and lifecycle control. The library distinguishes itself by offering a complete set of map features as individual React components that automatically adapt to light and dark themes. It includes components for interactive map rendering with zero configuration, marker placement with popups a
Renders hundreds or thousands of markers as GeoJSON layers on the WebGL canvas for high performance.
MUI X is a collection of advanced React UI components for building data-rich applications, including a data grid, charting library, date and time pickers, scheduler, and tree view. The library is built with accessibility as a core principle, ensuring all components meet WCAG and WAI-ARIA standards for keyboard navigation and screen reader announcements. The components are designed for extensibility and performance. The data grid offers comprehensive data management with sorting, filtering, pagination, column pinning, row grouping, inline editing, and Excel export. The charting library support
Uses WebGL rendering to smoothly display dense chart data at high frame rates.
ui-grid ist eine Enterprise-Datengitter-Komponente für Angular-Anwendungen, die zur Anzeige tabellarischer Daten entwickelt wurde. Sie fungiert als interaktive Datentabelle, die Virtualisierung unterstützt, um die Leistung beim Rendern großer Datensätze aufrechtzuerhalten. Das Gitter bietet spezialisierte Funktionen für professionelles Datenmanagement, einschließlich Zeilengruppierung, Spaltenfixierung und Zustandspersistenz. Es ermöglicht die Organisation komplexer Datenhierarchien und die Transformation flacher Datensätze in gruppierte oder Baumstrukturen. Die Komponente deckt ein breites Spektrum an Datenverwaltungsfunktionen ab, einschließlich In-Place-Zellenbearbeitung, Spalten-Neuanordnung und der Möglichkeit, Daten in externe Dateien zu importieren und zu exportieren. Sie enthält zudem Unterstützung für Tastaturnavigation und mehrsprachige Lokalisierung.
Renders high volumes of data with a focus on smooth performance and scrolling using virtualization.
Glide Data Grid ist ein virtualisiertes Datengitter für React und TypeScript, das die HTML Canvas API nutzt, um Millionen von Zellen flüssig darzustellen. Es ist als barrierefreie Datentabelle konzipiert, die auch bei der Anzeige und Navigation durch riesige Datensätze hohe Bildraten beibehält. Das Projekt zeichnet sich durch eine Canvas-basierte Rendering-Architektur aus, die Lazy Rendering und eine benutzerdefinierte Zeichen-API verwendet. Dies ermöglicht spezialisierte Zellinhalte und datengesteuertes Styling, das Standard-DOM-Update-Zyklen umgeht, um eine hohe Performance zu gewährleisten. Das Gitter bietet umfassende Layout- und Datenverwaltungsfunktionen, einschließlich Zellzusammenführung, fixierter Spalten, variabler Zeilenhöhen und automatischer Spaltenbreitenberechnung. Es enthält zudem integrierte Unterstützung für Zellbearbeitung, Elementauswahl und Datensuche innerhalb des Gitters.
Renders millions of rows at high frame rates with smooth scrolling and fast visual updates.
ArrayFire ist ein hardware-agnostisches Compute-Framework und eine JIT-kompilierte Tensor-Engine für numerische Hochleistungsberechnungen. Es dient als GPU-Bibliothek für numerische Berechnungen und Toolkit für parallele Signalverarbeitung, das Hardware-Backends abstrahiert und es ermöglicht, denselben Code auf verschiedenen GPU-Architekturen und CPUs auszuführen. Das Projekt zeichnet sich durch eine JIT-Engine aus, die Ausdruckskompilierung verwendet, um Operationen zu verschmelzen und den Speicher-Overhead zu minimieren. Es nutzt einen verzögerten Ausführungsgraphen zur Optimierung von Berechnungsketten und bietet Interoperabilitäts-Primitive, um Daten und Ausführungskontexte mit externen Compute-Plattformen wie CUDA und OpenCL zu teilen. Die Bibliothek deckt ein breites Spektrum an Fähigkeiten ab, einschließlich paralleler linearer Algebra, digitaler Signalverarbeitung und beschleunigter Computer Vision. Sie bietet Werkzeuge für die Implementierung von maschinellem Lernen, Simulationen für Finanzmodelle und die Lösung partieller Differentialgleichungen für physikalische Systemsimulationen. Das Tensor-Managementsystem verwaltet die Zuweisung mehrdimensionaler Arrays, Slicing sowie Datentransfers zwischen Host und Gerät.
Produces high-performance visual representations of data using accelerated rendering libraries.
Visual Insights ist eine Plattform für automatisierte explorative Datenanalyse und ein Tool für kausale Inferenz, das entwickelt wurde, um Muster sowie Ursache-Wirkungs-Zusammenhänge in Datensätzen zu entdecken. Es fungiert als interaktive Datenvisualisierungsbibliothek, die einen Grammar-of-Graphics-Ansatz verwendet, um mehrdimensionale Diagramme und Dashboards zu generieren. Das Projekt zeichnet sich durch eine natürlichsprachliche Schnittstelle aus, die Fragen in Klartext mithilfe eines Sprachmodells in Datenantworten und Visualisierungen übersetzt. Es bietet ein spezialisiertes Framework für kausale Entdeckung und Inferenz, das es Benutzern ermöglicht, Variablenverknüpfungen durch interaktive Kausaldiagramme zu identifizieren und What-if-Analysen zur Validierung von Hypothesen durchzuführen. Die Plattform deckt ein breites Spektrum an Funktionen ab, darunter visuelle Datenbereinigung, statistische Profilerstellung und automatisierte Datensatztransformation. Sie unterstützt die Integration verschiedener Daten aus lokalen Dateien und Remote-Datenbanken und verfügt über eine leistungsstarke Verarbeitungs-Engine für die lokale Handhabung großer Datensätze. Zusätzlich ermöglicht das System die Einbettung interaktiver Analysekomponenten in Webanwendungen und Notebooks.
Utilizes a high-performance computing engine to efficiently process and visualize large amounts of data on local machines.
This project is a utility library for the Google Maps SDK for Android, providing a suite of specialized tools for rendering geospatial data, calculating spherical geometry, and visualizing map markers and heatmaps. It serves as a helper collection to handle complex geospatial tasks within Android applications. The library features a marker clustering tool to group nearby markers into single icons and a map data visualizer for generating heatmaps based on the intensity and distribution of geographic points. It also includes a polyline encoding tool for compressing coordinate sequences into com
Provides high-performance, customizable markers by associating map instances with specific identifiers.
ChartGPU is a high-performance visualization library designed to render large-scale datasets and real-time data streams using hardware acceleration. It functions as a component-based tool that integrates into declarative user interfaces, allowing developers to build responsive, themeable charts that maintain smooth interaction even when processing massive amounts of information. The library distinguishes itself through a specialized rendering engine that employs screen-space binning and zoom-aware data resampling to manage dense datasets. It provides advanced interactive capabilities, includi
Renders massive datasets using hardware acceleration to maintain smooth interaction and high frame rates.