Overview

D3.js

Stacks1.9K

Followers1.7K

Votes653

GitHub Stars111.7K

Forks22.9K

SVG.js

Stacks11

Followers12

Votes0

GitHub Stars11.5K

Forks1.1K

D3.js vs SVG.js: What are the differences?

Introduction

In this Markdown code, we will discuss the key differences between D3.js and SVG.js, two popular libraries used for creating interactive graphics on the web.

D3.js: D3.js, also known as Data-Driven Documents, is a JavaScript library that provides a set of tools for manipulating data and creating data visualizations. It is widely used for creating complex and dynamic visuals by binding data to the Document Object Model (DOM) in HTML.
SVG.js: SVG.js is a lightweight JavaScript library specifically designed for working with Scalable Vector Graphics (SVG). It simplifies the creation and manipulation of SVG elements in HTML by providing an intuitive API that closely resembles the native SVG syntax.
Approach to Graphics Creation: D3.js follows a declarative approach, where developers define the desired outcome and let the library handle the rendering and animation. On the other hand, SVG.js takes an imperative approach, allowing developers to directly manipulate SVG elements using a simpler and more intuitive API.
Learning Curve: D3.js has a steeper learning curve due to its extensive functionality and more complex syntax. It requires a deeper understanding of JavaScript and SVG to use effectively. In contrast, SVG.js has a shallower learning curve, making it easier to get started with for beginners or developers who prefer a simpler approach.
Community and Ecosystem: D3.js has a larger community and a vast ecosystem of plugins and resources due to its popularity and wide usage. It has been around for a longer time and has been adopted by many data visualization projects. SVG.js, although not as widely adopted, still has an active community and a growing ecosystem of plugins and examples.
Use Cases: D3.js is particularly suited for creating highly customized and interactive data visualizations, such as complex charts, graphs, and maps. It provides fine-grained control over the rendering and behavior of elements. SVG.js, on the other hand, is more suitable for simpler graphics, animations, and interactive effects that primarily rely on SVG elements.

In Summary, D3.js and SVG.js differ in their approach to graphics creation, learning curve, community and ecosystem, and use cases. While D3.js is more complex and powerful, SVG.js offers a simpler and more beginner-friendly experience, while still enabling the creation of dynamic SVG graphics.

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Advice on D3.js, SVG.js

Ayaskant

SSE-II at Akamai

Oct 25, 2019

Needs advice

I want to get suggestions on these 2 open source js libraries (D3.js & echarts) that help in creating charts or graphs on the UI. Which one will be better for bar graphs. Which is easy to learn and start with? Which provides better features and community support?

My requirements are 1 - Plot data in X-Y axis graph where x-axis will present time till seconds level and Y-Axis will present the data corresponding to that time.

2 - Zoom-in and zoom out feature.

55.9k views55.9k

Comments

Detailed Comparison

D3.js	SVG.js
It is a JavaScript library for manipulating documents based on data. Emphasises on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework.	The lightweight library for manipulating and animating SVG. It has no dependencies and aims to be as small as possible.
Declarative Approach for Individual Nodes Manipulation; Functions Factory; Web Standards; Built-in ELement Inspector to Debug; Uses SVG, Canvas, and HTML; Data-driven approach to DOM Manipulation; Voronoi Diagrams; Maps and topo.	Animations on size, position, transformations, color,... ; Painless extension thanks to the modular structure; Various useful plugins available; Unified api between shape types with move, size, center, ...; Binding events to elements; Full support for opacity masks and clipping paths; Text paths, even animated; Element groups; Dynamic gradients and patterns
Statistics
GitHub Stars 111.7K	GitHub Stars 11.5K
GitHub Forks 22.9K	GitHub Forks 1.1K
Stacks 1.9K	Stacks 11
Followers 1.7K	Followers 12
Votes 653	Votes 0
Pros & Cons
Pros 195 Beautiful visualizations 103 Svg 92 Data-driven 81 Large set of examples 61 Data-driven documents Cons 11 Beginners cant understand at all 6 Complex syntax	No community feedback yet
Integrations
JavaScript React Native AngularJS React Bootstrap	JavaScript

What are some alternatives to D3.js, SVG.js?

Underscore

A JavaScript library that provides a whole mess of useful functional programming helpers without extending any built-in objects.

Deno

It is a secure runtime for JavaScript and TypeScript built with V8, Rust, and Tokio.

Highcharts

Highcharts currently supports line, spline, area, areaspline, column, bar, pie, scatter, angular gauges, arearange, areasplinerange, columnrange, bubble, box plot, error bars, funnel, waterfall and polar chart types.

Plotly.js

It is a standalone Javascript data visualization library, and it also powers the Python and R modules named plotly in those respective ecosystems (referred to as Plotly.py and Plotly.R). It can be used to produce dozens of chart types and visualizations, including statistical charts, 3D graphs, scientific charts, SVG and tile maps, financial charts and more.

Chart.js

Visualize your data in 6 different ways. Each of them animated, with a load of customisation options and interactivity extensions.

Recharts

Quickly build your charts with decoupled, reusable React components. Built on top of SVG elements with a lightweight dependency on D3 submodules.

ECharts

It is an open source visualization library implemented in JavaScript, runs smoothly on PCs and mobile devices, and is compatible with most current browsers.

ZingChart

The most feature-rich, fully customizable JavaScript charting library available used by start-ups and the Fortune 100 alike.

amCharts

amCharts is an advanced charting library that will suit any data visualization need. Our charting solution include Column, Bar, Line, Area, Step, Step without risers, Smoothed line, Candlestick, OHLC, Pie/Donut, Radar/ Polar, XY/Scatter/Bubble, Bullet, Funnel/Pyramid charts as well as Gauges.

CanvasJS

Lightweight, Beautiful & Responsive Charts that make your dashboards fly even with millions of data points! Self-Hosted, Secure & Scalable charts that render across devices.