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MJML VS Plotly

Compare MJML VS Plotly and see what are their differences

InboxAlly
Enterprise Email Warmup. Sender Domain Reputation Repair Tool to get out of spam and see open rates more than double in 4 to 14 days. We engage with your emails to teach mailbox providers not to send your email to the spam or the promotions folder. featured
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MJML logo MJML

The open source framework for responsive emails

Plotly logo Plotly

Low-Code Data Apps
  • MJML Landing page
    Landing page //
    2019-01-26
  • Plotly Landing page
    Landing page //
    2023-07-31

MJML features and specs

  • Responsive Design
    MJML is specifically designed to create responsive email templates that work well across various devices and email clients.
  • Ease of Use
    MJML uses a simplified markup language, making it easier for developers to create complex email designs without deep knowledge of HTML and CSS.
  • Community and Support
    MJML has a strong community and support system, including comprehensive documentation and numerous examples to help users get started.
  • Cross-Client Compatibility
    Emails created with MJML are tested for compatibility across a wide range of email clients, reducing the effort needed for testing and adjustments.
  • Customization and Flexibility
    MJML offers a variety of customizable components that allow developers to tailor emails to their specific needs.
  • Template Reusability
    MJML makes it easy to create reusable templates, which can save time and maintain consistency in email campaigns.
  • Integration
    MJML can be integrated with various development tools and workflows, which enhances productivity.

Possible disadvantages of MJML

  • Learning Curve
    Although easier than raw HTML/CSS for emails, MJML still requires learning a new syntax and understanding its components.
  • Limited Customization
    It may not offer as much flexibility as hand-coded HTML/CSS for emails, particularly for very unique or custom designs.
  • Dependency
    Using MJML adds another dependency to your project, which could complicate the build process and dependency management.
  • Performance
    Rendering complex MJML templates might be slower compared to hand-coded alternatives.
  • Error Handling
    MJML’s error messages can sometimes be vague, making it challenging to debug issues.
  • Size of Output
    The HTML output generated by MJML can be verbose, potentially leading to larger email sizes.
  • Browser and Client Specific Issues
    While MJML handles most cross-client compatibility, there can still be occasional issues that require manual adjustments.

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.

MJML videos

+ Add

Build Responsive Emails With MJML

More videos:

  • Review - Start to build responsive emails with MJML

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 MJML and Plotly)

MJML

Plotly

Email Marketing
100 100%
Email Marketing
0% 0
Data Visualization
0 0%
Data Visualization
100% 100
Email Newsletters
100 100%
Email Newsletters
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100

User comments

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Reviews

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

MJML Reviews

11 Best Free HTML Email Template Builders & Editors (Reviewed & Compared)
MJML is a markup language. They have an open-source server that generates high-quality responsive HTML for emails.
Source: www.emailvendorselection.com

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, MJML should be more popular than Plotly. It has been mentiond 94 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.

MJML mentions (94)

  • Easier Responsive Emails for Umbraco Forms with MJML
    MJML (Mailjet Markup Language) is a powerful open-source framework designed to simplify the creation of responsive email templates. Instead of manually coding complex HTML tables and inline styles, MJML offers an intuitive, component-based syntax that automatically generates well-structured and mobile-friendly emails. - Source: dev.to / 3 months ago
  • A guide to the best email editing tools
    MJML is a markup language that creates responsive email templates. It is intuitive in the sense that its markup is rendered into responsive HTML for any device and email client. - Source: dev.to / 6 months ago
  • Show HN: Sendune – open-source HTML email designer
    } Can be easily stored in Postgres jsonb. Very easy to add Reacjs base widgets like mentioning, media, diagrams, etc The drawback is that you can't design the exactly the same pixel perfect template. The better abstraction is MJML - https://mjml.io/ With slatejs/platejs json format you can copy&paste your editings across various assets in CRM, knowledge base, etc Was thinking about using something similar to... - Source: Hacker News / 10 months ago
  • Show HN: Sendune – open-source HTML email designer
    You can use MJML - https://mjml.io/ - which abstracts away a lot of the ugliness and Outlook hacks. - Source: Hacker News / 10 months ago
  • Modernizing Emails: Innovations for Efficient Handling in Distributed Systems
    The email service is built with Symfony and its templating engine, Twig. Templates are written in MJML markup, an email framework that helps us address the first problem we mentioned. Twig allows us to pass the data to the MJML template without breaking the MJML structure. After the data is rendered, we send the result to a small MJML service that converts the MJML markup to HTML. Here is an example of a template:. - Source: dev.to / almost 3 years ago
View more

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 / about 1 month 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 / 3 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 / 5 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 / 11 months 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 MJML and Plotly, you can also consider the following products

Stripo - Stripo is an all-in-one email design platform. We enable our clients to build emails of any complexity, including interactive AMP emails, really fast and easy.

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.

BeeFree.io - Bee is MailUp's drag-&-drop editor for responsive design emails.

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

HTMLEmail.io - Responsive HTML email templates for startups & developers

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

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