React Dashboard Charting Libraries

This project is a community-driven knowledge base that serves as a centralized directory for the React and React Native ecosystems. It functions as a developer discovery portal, aggregating high-quality libraries, frameworks, and learning resources to assist in the research and selection of tools for modern web and mobile application development. The repository distinguishes itself through a hierarchical taxonomy that organizes a fragmented landscape of third-party software into functional domains. By utilizing markdown-based content curation, it provides a structured index that allows developers to navigate specific categories such as state management, routing, component libraries, and build tooling. This classification system is maintained through distributed contributions, ensuring the collection remains an up-to-date reference for the community. Beyond core frameworks and libraries, the directory covers a broad spectrum of development needs, including testing utilities, animation engines, internationalization tools, and specialized renderers. It also provides access to tutorials, design patterns, and real-world application examples to support developers across various stages of the software lifecycle. The entire collection is presented as a static documentation index, offering a human-readable format for quick exploration of the ecosystem.

react-chartjs-2 is a data visualization library that provides a set of React components to integrate the Chart.js library. It serves as a component-based charting interface for rendering dynamic data visualizations and graphs based on structured data sets. The project provides a declarative way to manage chart configurations and data updates. It maps component props to the underlying charting engine, allowing users to modify visual options and data dynamically to refresh displays. The library covers broader data visualization development, including the implementation of dynamic dashboards and the integration of charting tools into a component architecture.

This project is a declarative data visualization library that provides a composable suite of user interface components for rendering interactive charts. It functions as an SVG-based charting engine, allowing developers to construct complex visualizations by nesting modular building blocks such as axes, grids, legends, and data series within a unified layout. The library distinguishes itself through a highly responsive architecture that automatically reconciles layout changes and maps data domains to pixel coordinates using mathematical scale functions. It prioritizes performance through memoized property diffing and component isolation, ensuring that high-frequency data updates remain smooth. Furthermore, it offers extensive customization hooks, enabling developers to inject unique shapes, custom styles, and specialized labels into individual chart elements. Beyond its core composition model, the framework includes comprehensive tools for managing user interactions, such as tooltips and coordinate-aware event handling. It supports a wide range of axis configurations for both continuous and categorical data, alongside built-in accessibility features that respect system-level motion preferences. The library is built with TypeScript, providing generic data support and strongly-typed wrappers to ensure consistency during development.

Visx is a collection of modular, low-level primitives designed for building custom data visualizations within a React component architecture. It functions as a toolkit for mapping data to coordinate systems and geometric shapes, allowing developers to construct bespoke charts and graphs that integrate directly into the standard component lifecycle. The library utilizes a decoupled package architecture, enabling the use of specific visualization utilities without requiring the entire framework. By leveraging established mathematical primitives for geometric calculations and functional data transformation, it provides a declarative approach to defining visual structures. All visual elements are rendered as standard web graphics, mapping component properties directly to native document object model nodes. This framework supports the development of highly tailored analytical interfaces and interactive information design. It provides the necessary building blocks for web graphics engineering, allowing for full control over rendering logic and layout requirements in complex data-driven applications.

Chart.js is a declarative data visualization framework that renders interactive, responsive charts directly onto an HTML5 canvas element. It functions as a configuration-driven engine, transforming structured datasets into complex graphical representations by merging user-defined settings with global defaults. The library utilizes a high-performance rendering pipeline that executes drawing commands during each animation frame to maintain smooth visual feedback. The project distinguishes itself through a modular, extensible architecture that allows developers to register custom scales, controllers, and plugins to modify the internal lifecycle of a chart. This design enables the creation of specialized visual behaviors and the integration of diverse data formats within a single view. To ensure responsiveness and efficiency, the engine includes built-in decimation algorithms that filter large datasets, preventing performance degradation when rendering high volumes of information. Beyond its core rendering capabilities, the library provides a comprehensive suite of tools for managing axes, scales, and multi-series data comparisons. Developers can precisely control the appearance of grid lines, tick labels, and stacking behaviors to ensure data remains readable across various screen sizes. The system also supports advanced interaction handling, allowing for the identification of specific data points under the cursor to provide immediate feedback to the end user.

react-chartjs-2 is a data visualization library that provides a set of React components acting as a wrapper for Chart.js. It allows for the rendering of interactive charts and graphs within a React application using a declarative approach. The library manages HTML5 canvas charting components by tying the lifecycle of Chart.js instances to the mounting and unmounting of the React component tree. It translates component props into the configuration objects required by the underlying engine to map datasets to visual elements. The project covers a range of frontend integration capabilities, including the development of data visualization dashboards, interactive reporting, and web application analytics.

D3 is a modular library providing low-level primitives for creating data-driven visualizations. It functions as a flexible framework that allows for direct control over visual presentation by mapping abstract data dimensions to graphical properties, such as position, color, and size, without imposing predefined chart abstractions. The library distinguishes itself by offering specialized tools for complex data representation, including algorithmic layouts for hierarchical structures and geographic projection utilities for mapping spherical coordinates. It also includes a comprehensive suite for managing user interactions, enabling the creation of interactive selection areas that respond to mouse and touch input. Beyond visualization, the project provides a collection of utilities for document manipulation and data processing. These tools allow developers to query elements, apply data-driven transformations, and perform operations such as ordering, grouping, and summarizing datasets to prepare them for rendering in vector or bitmap contexts.

vx is a declarative charting framework and SVG data visualization library. It serves as an integration layer that combines D3 mathematical scales and shapes with a component-based UI for rendering visualizations. The project provides a set of building blocks for constructing custom charts and diagrams using React components. It bridges mathematical data and visual representation by utilizing low-level primitives to manage scalable vector graphics without manual document object model manipulations. The library covers a broad capability surface including custom chart development, declarative SVG rendering, and the creation of interactive data dashboards.

react-vis is a declarative, component-based React data visualization library. It provides a framework of reusable building blocks for rendering interactive charts and graphs by mapping raw data to visual attributes such as position, color, and size. The system leverages D3 for its scaling and layout logic. The library is distinguished by its ability to handle complex data relationships, including hierarchical data via tree maps and circle packing, as well as multidimensional analysis using parallel axes and radar charts. It also supports network flow mapping to illustrate the volume and direction of data movement between nodes. The framework covers general charting capabilities such as histograms and circular renderings, alongside interactive exploration tools like data brushing, crosshairs, and tooltips. It includes systems for axis configuration, localized time labels, and the generation of color and size legends.

TanStack Table is a headless, framework-agnostic engine designed for building complex data grids and managing tabular state. By decoupling data processing logic from the visual rendering layer, it allows developers to implement custom user interfaces while offloading sophisticated operations like sorting, filtering, grouping, and pagination to a unified, performant core. The library distinguishes itself through its commitment to type safety and environment flexibility. It leverages strict type definitions to ensure data integrity across the entire application and utilizes an adapter pattern to maintain consistent behavior across different frontend runtimes. This architecture enables developers to manage table state and row interactions programmatically without being constrained by specific markup or styling requirements. Beyond core grid functionality, the project provides a comprehensive suite of utilities for managing application state, including support for server-side data synchronization, optimistic updates, and reactive data queries. It is built to handle large datasets and complex data manipulation tasks, offering a modular approach to frontend data processing that remains consistent regardless of the underlying framework.

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 shifts between different data states. The framework supports multiple rendering strategies, including SVG-based vector rendering and canvas-based rendering for high-performance data sets. Its capability surface covers responsive layout adjustments, interactive data rendering, and a theme-based system for custom data branding and visual consistency.

This project is a client-side rendering engine that transforms declarative, text-based syntax into visual diagrams directly within the browser. By utilizing a domain-specific language, it allows users to define complex structures—such as software architectures, process flows, and system behaviors—without the need for manual layout configuration. The library functions as a browser-based runtime that parses these definitions into intermediate abstract syntax trees, which are then processed by specialized engines to generate high-fidelity, resolution-independent graphics. The system distinguishes itself through a modular architecture that decouples diagram types into independent plugins, allowing for a wide range of visualizations including sequence diagrams, entity relationship models, and project timelines. To ensure security when processing untrusted input, the library supports sandboxed rendering within isolated frames. It also features automatic rendering capabilities, which monitor the document object model to detect and visualize diagram definitions embedded within standard web content. Beyond its core rendering engine, the project supports a documentation-as-code workflow by integrating with various development environments, productivity platforms, and content frameworks. This enables the inclusion of version-controlled, dynamic visuals in technical guides and wikis. The library is designed for flexible deployment, offering support for content delivery network integration to facilitate implementation without requiring local build processes.

BizCharts is a React charting library that wraps the G2 grammar of graphics, providing declarative React components for building interactive data visualizations. It bridges G2's imperative charting API with React's declarative component model, enabling chart creation through nested component composition without writing imperative code. The library distinguishes itself by mapping G2's grammar of graphics primitives directly to React component types, allowing chart series like line, bar, and scatter to be expressed as interchangeable React components. It synchronizes G2 chart instance creation, updates, and destruction with React component lifecycle hooks, and translates React component props into G2 configuration objects at runtime. An event bridge layer connects DOM events from G2 chart elements to React synthetic events, enabling standard React event handling for chart interactions. BizCharts supports a wide range of chart types with customizable appearance and interactive elements such as tooltips, hover, click, and zoom. It also provides an extension mechanism for adding custom chart behaviors and visual elements without modifying core components. The project includes migration guidance for moving existing visualizations to actively maintained libraries like G2Plot or G2.

This project is a React-based framework for constructing interactive, node-based visual interfaces. It provides a platform for building canvases where users define, connect, and organize logical processes, data pipelines, or complex workflows through a graphical interface. By utilizing a modular component architecture, it enables the development of low-code environments, visual programming tools, and interactive diagramming applications. The framework distinguishes itself through a declarative approach where state changes automatically synchronize with the visual representation of nodes and edges. It employs a coordinate-aware container that renders elements as scalable vector graphics, ensuring consistent visual quality across zoom levels. Developers can leverage an integrated event-driven layer to manage user gestures, alongside automated layout algorithms that organize graph elements in real time to improve readability. The system includes comprehensive utilities for managing node properties, connection handles, and nested hierarchies. It supports a wide range of applications, from data exploration and automated graph visualization to specialized use cases like real-time audio synthesis. The project is distributed as a library of components designed to facilitate the creation of custom, interactive graph editors within web applications.

DataV is a big screen visualization framework designed for high-impact data displays. It provides a collection of libraries for both Vue and React to build large-scale data dashboards featuring interactive charts and visual elements. The toolkit includes a specialized decoration kit of scalable vector graphics used to add borders and frames to professional data display screens. It focuses on complex data visualization, including the rendering of specialized charts such as water level and flight line maps. The framework covers a broad capability surface for data dashboard visualization, providing pre-made components to represent complex datasets and monitor performance indicators.

This project is a serverless service that generates dynamic, themeable visual summaries of software development activity. It functions as an automated metadata visualizer, transforming raw platform logs and repository metrics into resolution-independent vector graphics that can be embedded directly into markdown environments. The service distinguishes itself by offering highly configurable, query-parameter-driven rendering that allows users to customize the visual presentation of their coding patterns, language proficiency, and repository details. It supports both real-time generation via serverless functions and the creation of static image files through automated workflows, providing flexibility in how data is fetched and displayed. The platform aggregates disparate data points from multiple sources to provide comprehensive insights into development habits and project metadata. Users can deploy private instances of the service to maintain full control over caching strategies, authentication tokens, and rate limit management.

Glance is a self-hosted web portal designed to aggregate real-time data, system monitoring, and content feeds into a single, customizable dashboard. It functions as a centralized interface for managing internal tools and network services, allowing users to secure their portal with password authentication and define the application's visual identity and layout through structured configuration files. The platform is built on a modular widget engine that treats individual dashboard components as isolated units. This architecture enables users to arrange widgets into custom pages and columns, with each component independently fetching and rendering data from external sources, service status checks, or system interfaces. The system supports a wide range of integrations, including containerized workload monitoring, server resource tracking, and various web-based content feeds. Beyond its core monitoring capabilities, the application includes productivity utilities such as task management and custom search interfaces. It provides flexibility for advanced users through custom API data visualization, which allows for the transformation of raw JSON responses into formatted widgets using custom templates. The system is designed to operate behind reverse proxies and can be configured to interact directly with host-level interfaces and container runtimes.

Victory is a React data visualization library and composable visualization toolkit used to build interactive charts and graphs. It functions as an SVG charting framework that renders scalable data visualizations designed to maintain consistency across different web browsers and operating systems. The project provides a collection of reusable UI primitives that combine to form complex interactive data layouts. This component-based approach allows for the construction of sophisticated graphs by composing modular visualization elements within React applications.

This project is a React-based WebGL renderer that enables the creation of three-dimensional scenes using a declarative, component-driven architecture. It functions as a bridge between a component-based user interface library and a low-level graphics engine, allowing developers to manage lights, cameras, and geometry as standard elements within a reactive tree structure. The library distinguishes itself by treating the scene graph as a declarative hierarchy that synchronizes directly with application state and lifecycle events. It utilizes a custom reconciler to map component updates to object mutations, while a reflection-based system automatically binds component properties to underlying graphics objects. By integrating directly with the animation frame cycle, it ensures that visual updates remain synchronized with the render loop. Beyond core rendering, the project provides a normalized event system that translates pointer interactions into raycasting intersections for 3D objects. It supports the development of consistent graphical content across desktop and mobile browsers through a unified programming model, while using context-based patterns to manage scene-specific instances like cameras and renderers.

Twenty is a headless customer relationship management framework that enables developers to build, version, and deploy custom business applications using code. By utilizing a declarative approach to data modeling, the platform allows for the definition of custom objects, fields, and complex relationships directly within the source code. This schema-driven architecture automatically generates corresponding REST and GraphQL APIs, ensuring that data structures and interface components remain synchronized across development and production environments. The platform distinguishes itself through a modular, code-first development experience that avoids proprietary lock-in. Developers can extend core functionality by packaging custom server-side logic, automated workflows, and React-based user interface components. These extensions execute within sandboxed environments, providing secure, isolated runtime performance while maintaining granular control over data access and system resources. Beyond its core modeling capabilities, the platform includes a comprehensive suite of tools for business automation, integration, and team collaboration. It supports event-driven workflows that trigger actions based on record changes, scheduled tasks, or external webhooks, alongside AI-powered agents for data processing and conversational interaction. The system also provides robust developer tooling, including command-line scaffolding, containerized deployment support, and integrated CI/CD pipelines to manage the entire application lifecycle. The project is designed for self-hosting or cloud deployment, offering full data ownership and infrastructure control. Documentation and installation are facilitated through standard command-line interfaces, allowing teams to initialize projects, manage dependencies, and sync code changes in real time.