Overview

Plotly.js

Stacks399

Followers694

Votes69

GitHub Stars17.9K

Forks1.9K

Bokeh

Stacks95

Followers183

Votes12

GitHub Stars20.2K

Forks4.2K

Bokeh vs Plotly: What are the differences?

Introduction

Bokeh and Plotly are both interactive data visualization libraries that are commonly used in web applications. While they share some similarities, there are several key differences between the two.

Backend Infrastructure: The major difference between Bokeh and Plotly lies in their backend infrastructure. Bokeh is a server-based library that generates JavaScript in the client-side browser to create interactive visualizations. On the other hand, Plotly is API-based and can be used with different programming languages to generate visualizations.
Ease of Use: Bokeh provides a simplified and concise API that allows users to create visualizations with minimal code. It emphasizes ease of use and offers a wide range of pre-built plot types. Plotly, on the other hand, has a slightly steeper learning curve and requires a deeper understanding of the API and its different components.
Interactivity: Bokeh is primarily designed for creating interactive visualizations, with support for interactivity such as hover tooltips, zooming, panning, and selection tools. Plotly, on the other hand, offers a more extensive set of interactivity options, including linked brushing, animations, and even 3D plotting capabilities.
Offline vs. Online Usage: Bokeh supports both offline and online usage, meaning that you can generate visualizations without internet connectivity. Plotly, on the other hand, is built to work primarily in an online environment and requires an internet connection to retrieve data and create visualizations.
Community and Documentation: Bokeh has a growing community of users and developers, and it provides comprehensive documentation and examples to help users get started. Plotly, on the other hand, has a larger and more active community, with extensive documentation and a wide range of user-contributed examples and tutorials.
Cost and Licensing: Bokeh is an open-source library released under the BSD-3-Clause license, making it free to use and distribute. Plotly offers both open-source and commercial versions, with additional features available in the commercial version for enterprise users.

In Summary, Bokeh and Plotly are both powerful tools for creating interactive visualizations, but they differ in terms of their backend infrastructure, ease of use, interactivity options, offline/online usage, community support, and licensing.

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Detailed Comparison

Plotly.js	Bokeh
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.	Bokeh is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics, and affords high-performance interactivity over large or streaming datasets.
Feature parity with MATLAB/matplotlib graphing; Online chart editor; Fully interactive (hover, zoom, pan); SVG and WebGL backends; Publication-quality image export	interactive visualization library ; versatile graphics ; open source; https://github.com/bokeh/bokeh
Statistics
GitHub Stars 17.9K	GitHub Stars 20.2K
GitHub Forks 1.9K	GitHub Forks 4.2K
Stacks 399	Stacks 95
Followers 694	Followers 183
Votes 69	Votes 12
Pros & Cons
Pros 16 Bindings to popular languages like Python, Node, R, etc 10 Integrated zoom and filter-out tools in charts and maps 9 Great support for complex and multiple axes 8 Powerful out-of-the-box featureset 6 Beautiful visualizations Cons 18 Terrible document	Pros 12 Beautiful Interactive charts in seconds
Integrations
Python React MATLAB Jupyter Julia	Bootstrap Flask NGINX React Django Python Jupyter Tornado Streamlit

What are some alternatives to Plotly.js, Bokeh?

D3.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.

Highcharts

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Chart.js

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Recharts

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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.

AnyChart

AnyChart is a flexible JavaScript (HTML5) based solution that allows you to create interactive and great looking charts. It is a cross-browser and cross-platform charting solution intended for everybody who deals with creation of dashboard, reporting, analytics, statistical, financial or any other data visualization solutions.