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Highcharts VS Plotly

Compare Highcharts VS Plotly and see what are their differences

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Highcharts logo Highcharts

A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application

Plotly logo Plotly

Low-Code Data Apps
  • Highcharts Landing page
    Landing page //
    2023-03-16
  • Plotly Landing page
    Landing page //
    2023-07-31

Highcharts features and specs

  • Customization
    Highcharts provides extensive options to customize chart appearance and functionality, allowing for a tailored and specific data visualization experience.
  • Cross-Browser Compatibility
    Highcharts ensures compatibility across a wide range of browsers, making charts accessible to users regardless of their browser preferences.
  • Wide Range of Chart Types
    Offers a broad spectrum of chart types, including line, bar, pie, scatter, and more, catering to various data visualization needs.
  • Interactive Features
    Includes numerous interactive features such as tooltips, zooming, and clickable points, enhancing user engagement with the data.
  • Strong Community and Support
    Has an active community and provides extensive documentation, forums, and professional support options to assist users in overcoming challenges.
  • Performance
    Optimized for high performance, allowing for the rendering of large datasets without significant lag or performance issues.
  • Exporting and Sharing
    Built-in options for exporting charts to various formats (PNG, JPEG, PDF, etc.) and sharing them easily.

Possible disadvantages of Highcharts

  • Cost
    Highcharts is not free for commercial use, which may be a drawback for small businesses or individual developers with limited budgets.
  • Steep Learning Curve
    Despite comprehensive documentation, the abundance of features and customization options can result in a steeper learning curve for new users.
  • Dependency on JavaScript
    As a JavaScript library, Highcharts requires a solid understanding of JavaScript, making it less accessible for developers not familiar with the language.
  • Limited Free Support
    While there is a free support forum, professional support options are paid, which can be a limitation for users needing urgent assistance without extra costs.
  • Mobile Responsiveness
    Although Highcharts provides some support for mobile responsiveness, achieving optimal performance and displays on all device types may require additional customization.

Plotly features and specs

  • Interactivity
    Plotly offers highly interactive plots that allow users to pan, zoom, and hover over data points for more information. This enhances the user experience and provides deeper insights.
  • High-quality visualizations
    It provides aesthetically pleasing and highly customizable charts, making it suitable for publication-quality visuals.
  • Versatility
    Plotly supports multiple chart types including line charts, scatter plots, bar charts, and 3D plots, making it suitable for a wide range of applications.
  • Python integration
    Plotly is well-integrated with Python and works seamlessly with other popular data science libraries like Pandas, NumPy, and Scikit-learn.
  • Web-based
    The plots can be easily embedded in web applications or dashboards, making it ideal for sharing insights over the internet.
  • Open-source
    Plotly offers an open-source version, which allows users to create and share visualizations without any cost.

Possible disadvantages of Plotly

  • Performance
    Rendering very large datasets can sometimes be slow, which may not be suitable for real-time data visualization requirements.
  • Learning curve
    Even though the library is well-documented, the extensive range of features can have a steep learning curve for beginners.
  • Cost for advanced features
    While the basic functionality is free, more advanced features, such as export to certain formats and additional customizable options, require a paid subscription.
  • Dependency management
    Plotly has a number of dependencies that need to be managed properly, which can sometimes complicate the setup process.
  • Complexity
    For simple visualizations, Plotly might be overkill and simpler libraries like Matplotlib or Seaborn could be more appropriate.

Analysis of Highcharts

Overall verdict

  • Highcharts is a strong choice for those seeking a robust and feature-rich charting library. Its popularity among developers and businesses stems from its reliability and comprehensive feature set.

Why this product is good

  • Highcharts is considered good because it offers a wide range of chart types and is highly customizable. It is known for its detailed documentation, ease of use, and cross-platform compatibility. Additionally, Highcharts provides extensive support and a variety of integrations with popular frameworks, making it a versatile choice for developers.

Recommended for

  • Developers looking for a user-friendly and customizable charting library.
  • Projects that require extensive interactive data visualizations.
  • Businesses that need a reliable and professionally supported charting solution.
  • Teams using web technologies and frameworks like Angular, React, or Vue for front-end development.

Analysis of Plotly

Overall verdict

  • Overall, Plotly is a strong choice for those looking to create dynamic and interactive data visualizations, thanks to its range of features and ease of integration with web technologies.

Why this product is good

  • Plotly is considered good because it offers a comprehensive suite of tools for creating interactive visualizations that can be used in web applications, reports, and dashboards. It supports many different types of plots, is easy to use for both beginners and experienced developers, and integrates well with popular programming languages like Python, R, and JavaScript.

Recommended for

    Plotly is recommended for data scientists, analysts, and developers who need to create interactive and visually appealing data visualizations. It's particularly useful for those who work with Python or R and want the ability to embed their visualizations in web applications or dashboards.

Highcharts videos

+ Add

Angular 2 & HighCharts Quick-Tip: Dynamic Data & Draggable Points (2016)

More videos:

  • Tutorial - How to define the custom colors for Highcharts?
  • Review - Data Visualization HighCharts

Plotly videos

+ Add

Create Real-time Chart with Javascript | Plotly.js Tutorial

More videos:

  • Review - Introducing plotly.py 3.0
  • Review - Is Plotly The Better Matplotlib?
  • Tutorial - Plotly Tutorial 2021
  • Review - Data Visualization as The First and Last Mile of Data Science Plotly Express and Dash | SciPy 2021

Category Popularity

0-100% (relative to Highcharts and Plotly)

Highcharts

Plotly

Data Dashboard
55 55%
Data Dashboard
45% 45
Data Visualization
47 47%
Data Visualization
53% 53
Charting Libraries
54 54%
Charting Libraries
46% 46
Business Intelligence
57 57%
Business Intelligence
43% 43

User comments

Share your experience with using Highcharts and Plotly. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Highcharts and Plotly

Highcharts Reviews

6 JavaScript Charting Libraries for Powerful Data Visualizations in 2023
However, you might need to pay for additional packages to get exactly what you’re looking for. The Highcharts Core package includes all the essentials (like line, bar, area, and pie charts) but Maps, Gantt, and Stock chart packages are all extra. In terms of cost, this makes Highcharts somewhat less scalable, depending on the budget available for your project.
Source: embeddable.com
15 JavaScript Libraries for Creating Beautiful Charts
Highcharts is another very popular library for building graphs. It comes loaded with many different types of cool animations that are sufficient to attract many eyeballs to your website. Just like other libraries, Highcharts comes with many pre-built graphs like spline, area, areaspline, column, bar, pie, scatter, etc. The charts are responsive and mobile-ready. Besides,...
Source: www.sitepoint.com
Best Data Visualization Tools
For companies that want to embed interactive visualizations in their online content, look no further than Datawrapper. Highcharts is another great option for embedding interactive content into your sites, though it’s not as easy for non-specialists as Datawrapper.
Source: neilpatel.com
Top 10 JavaScript Charting Libraries for Every Data Visualization Need
Highcharts is one of the most comprehensive and popular JavaScript charting libraries based on HTML5, rendering in SVG/VML. It is lightweight, supports a wide range of diverse chart types, and ensures high performance.
Source: hackernoon.com
The Best Data Visualization Tools - Top 30 BI Software
Highcharts is a battle-tested SVG-based, multi-platform charting library that has been actively developed since 2009. Its JavaScript API integrates easily, and features robust documentation, advanced responsiveness and industry-leading accessibility support. You can add interactive, mobile-optimized charts to your web and mobile projects. Charts are rendered in SVG and a VML...
Source: improvado.io

Plotly Reviews

Best 8 Redash Alternatives in 2023 [In Depth Guide]
Plotly is specifically designed for companies who want to build and deploy analytic applications like dashboards using Python, Julia, or R without needing DevOps or Javascript developers.
Source: www.datapad.io
5 Best Python Libraries For Data Visualization in 2023
Plotly is a web-based data visualization toolkit that comes with unique functionalities such as dendrograms, 3D charts, and also contour plots, which is not very common in other libraries. It has a great API offering scatter plots, line charts, bar charts, error bars, box plots, and other visualizations. Plotly can even be accessed from a Python Notebook.
Source: www.technotification.com
Top 8 Python Libraries for Data Visualization
Plotly is a free open-source graphing library that can be used to form data visualizations. Plotly (plotly.py) is built on top of the Plotly JavaScript library (plotly.js) and can be used to create web-based data visualizations that can be displayed in Jupyter notebooks or web applications using Dash or saved as individual HTML files. Plotly provides more than 40 unique...
Source: www.geeksforgeeks.org
5 top picks for JavaScript chart libraries
Plotly is a graphing library that’s available for various runtime environments, including the browser. It supports many kinds of charts and graphs that we can configure with a variety of options.
Source: blog.logrocket.com

Social recommendations and mentions

Based on our record, Plotly seems to be more popular. It has been mentiond 33 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Highcharts mentions (0)

We have not tracked any mentions of Highcharts yet. Tracking of Highcharts recommendations started around Mar 2021.

Plotly mentions (33)

  • Python for Data Visualization: Best Tools and Practices
    Plotly is perfect for interactive visualizations. You can create interactive charts and graphs that allow users to hover, click, and zoom in. Plotly is also great for web-based visuals, making it easy to share your findings online. - Source: dev.to / 3 months ago
  • Generative AI Powered QnA & Visualization Chatbot
    Front End: A React application that leverages React-Chatbotify library to easily integrate a chatbot GUI. It also uses the Plotly library to display the charts/visualizations. The generative AI implementation and details are entirely abstracted from the front end. The front-end application depends on a single REST endpoint of the backend application. - Source: dev.to / 5 months ago
  • Build a Stock Dashboard in less than 40 lines of Python code!🤓
    In this tutorial, Mariya Sha will guide you through building a stock value dashboard using Taipy, Plotly, and a dataset from Kaggle. - Source: dev.to / 7 months ago
  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / about 1 year ago
  • Python equivalent to power bi/power query?
    For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: over 1 year ago
View more

What are some alternatives?

When comparing Highcharts and Plotly, you can also consider the following products

D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.

Chart.js - Easy, object oriented client side graphs for designers and developers.

Google Charts - Interactive charts for browsers and mobile devices.

RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...

AnyChart - Award-winning JavaScript charting library & Qlik Sense extensions from a global leader in data visualization! Loved by thousands of happy customers, including over 75% of Fortune 500 companies & over half of the top 1000 software vendors worldwide.

Geckoboard - Get to know Geckoboard: Instant access to your most important metrics displayed on a real-time dashboard.

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