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Parcel VS Plotly

Compare Parcel VS Plotly and see what are their differences

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Parcel logo Parcel

Blazing fast, zero configuration web application bundler

Plotly logo Plotly

Low-Code Data Apps
  • Parcel Landing page
    Landing page //
    2021-12-13
  • Plotly Landing page
    Landing page //
    2023-07-31

Parcel features and specs

  • Zero Configuration
    Parcel requires minimal to no configuration to get started, making it extremely user-friendly, especially for beginners or small projects.
  • Fast Bundling
    Parcel uses worker threads to parallelize tasks, which significantly speeds up the bundling process compared to other bundlers that do not use this approach.
  • Out-of-the-box support for many file types
    Parcel supports many file types (e.g., JavaScript, CSS, HTML, images) right out-of-the-box without needing additional plugins or configurations.
  • Hot Module Replacement (HMR)
    Parcel offers built-in HMR, allowing developers to see changes in real-time without needing to refresh the browser, leading to a faster development cycle.
  • Tree Shaking
    Parcel automatically performs tree shaking, removing unused code from the production build to reduce file sizes, which can improve loading times.
  • Code Splitting
    Parcel has automatic code splitting capabilities which help to improve performance by loading only the necessary assets.
  • Extensible via Plugins
    Parcel’s plugin system allows developers to extend its functionality easily if custom or additional features are needed.

Possible disadvantages of Parcel

  • Community and Ecosystem
    The community and ecosystem around Parcel are smaller compared to other bundlers like Webpack, so finding solutions and third-party plugins might be more challenging.
  • Limited Customization
    While the zero-config aspect is beneficial, it also means there are fewer customization options out-of-the-box, which might be limiting for complex projects needing specific configurations.
  • Performance with Large Projects
    For very large projects, Parcel's performance can become a bottleneck, particularly when it comes to initial build times.
  • Documentation
    The documentation, while improving, is not as comprehensive as some other tools, making it harder for developers to find detailed information when they encounter issues.
  • Dependency Bloat
    Parcel can sometimes include more dependencies than necessary in the final bundle, potentially increasing the final bundle size.

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 Parcel

Overall verdict

  • Parcel is a good choice for developers looking for a hassle-free, efficient, and beginner-friendly bundler. Its minimal configuration approach and speed make it ideal for small to medium-sized projects. However, for highly complex projects that require intricate and highly customized build processes, other bundlers might be more suitable due to their advanced configuration capabilities.

Why this product is good

  • Parcel is a web application bundler that is appreciated for its simplicity and zero-config philosophy. It automatically detects the files needed for a project without requiring a complex configuration file. Its fast performance is attributed to parallelization and efficient caching. Additionally, Parcel offers out-of-the-box support for JavaScript, CSS, HTML, asset management, and various types of file transformations, making it a versatile tool for web developers.

Recommended for

  • Developers new to module bundlers or looking for an easy-to-setup tool.
  • Projects that value speed and simplicity in their build processes.
  • Developers who need a bundler capable of handling multiple asset types with minimal configuration.
  • Teams that prefer convention over configuration and want to get started quickly without diving deep into complex bundler settings.

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.

Parcel videos

+ Add

Danby Parcel Guard Smart Mailbox blogger Review

More videos:

  • Review - PARCEL MOVIE REVIEW | SASWATA CHATTERJEE | RITUPARNA SENGUPTA | RUPAM'S REVIEW
  • Review - Le Parcel Box review

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 Parcel and Plotly)

Parcel

Plotly

Web Application Bundler
100 100%
Web Application Bundler
0% 0
Data Visualization
0 0%
Data Visualization
100% 100
JS Build Tools
100 100%
JS Build Tools
0% 0
Charting Libraries
0 0%
Charting Libraries
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 Parcel and Plotly

Parcel Reviews

Rollup v. Webpack v. Parcel
Parcel's caching feature sees dramatically decreases in time consumption after the initial run. For frequent, small changes, in smaller projects **Parcel*8 is a great choice.
Source: x-team.com
If you’ve ever configured Webpack, Parcel will blow your mind!
document.body.className = document.body.className.replace(/(^|\s)is-noJs(\s|$)/, "$1is-js$2")HomepageHomepageJavascriptBecome a memberSign inGet startedIf you’ve ever configured Webpack, Parcel will blow your mind!And how to hit the ground running with Parcel.Ibrahim ButtBlockedUnblockFollowFollowingMar 16, 2018Click here to share this article on LinkedIn »Zero...
Source: medium.com
First impressions with Parcel JS
The big selling point of Parcel though is that it offers a zero configuration experience. This means all the features are available out of the box! It also boasts blazing fast bundle times 👟 You won’t be configuring how Parcel works or having to draft in various plugins to get started. If you do need something, Parcel magically detects this and will pull in stuff for you on...
Source: codeburst.io
Parcel vs webpack - Jakob Lind
Parcel has made their own benchmarks of Parcel and other bundlers. Parcel has been criticized because they have not made the benchmarks open source. People cannot verify that the benchmarks are true when they are not open source.
Source: blog.jakoblind.no

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, Parcel should be more popular than Plotly. It has been mentiond 115 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.

Parcel mentions (115)

  • JavaScript Awesome Package
    Parcel - Blazing fast, zero configuration web application bundler. - Source: dev.to / 7 months ago
  • Nix + pnpm + Parcel + lydell/elm-safe-virtual-dom
    Pnpm and Parcel are used to build the application in nix/app.nix. - Source: dev.to / 7 months ago
  • Migrating a JavaScript Project from Prettier and ESLint to BiomeJS
    Https://parceljs.org/ is another. It even supports languages like `` out of the box which is pretty cool. IIRC it downloads necessarily plugins on the fly. - Source: Hacker News / over 1 year ago
  • Create React App is Deprecated – What’s Next ?
    Parcel is another alternative that requires zero configuration and is super fast. If you want a simple React setup without any hassle, Parcel is a great choice. - Source: dev.to / over 1 year ago
  • Bun 1.2 Is Released
    From its documentation [1] it looks a lot like a parceljs replacement [2], i.e. a zero config bundler which processes and bundles the dependencies in .html pages. So great for simple websites, not for replacing an entire Vite stack. [1] https://bun.sh/docs/bundler/fullstack [2] https://parceljs.org. - Source: Hacker News / over 1 year ago
View more

Plotly mentions (34)

  • How to Analyze 47 Million Hacker News Posts: A Data Scientist's Dream Dataset Just Got Better
    Let's dive into some practical examples. First, you'll need to set up your environment with the right tools. I recommend using pandas for data manipulation and plotly for visualization. - Source: dev.to / 6 months ago
  • 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 / over 1 year 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 / over 1 year 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 / almost 2 years 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 2 years ago
View more

What are some alternatives?

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

Webpack - Webpack is a module bundler. Its main purpose is to bundle JavaScript files for usage in a browser, yet it is also capable of transforming, bundling, or packaging just about any resource or asset.

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.

rollup.js - Rollup is a module bundler for JavaScript which compiles small pieces of code into a larger piece such as application.

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

AfterShip - AfterShip is the shipment tracking API for ecommerce businesses and marketplaces.

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

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