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Squoosh VS Plotly

Compare Squoosh VS Plotly and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Squoosh logo Squoosh

Compress and compare images with different codecs, right in your browser

Plotly logo Plotly

Low-Code Data Apps
  • Squoosh Landing page
    Landing page //
    2024-08-13
  • Plotly Landing page
    Landing page //
    2023-07-31

Squoosh features and specs

  • Free to Use
    Squoosh is a free web application, which makes it accessible to anyone without the need for a subscription or payment.
  • User-Friendly Interface
    The application features an intuitive and easy-to-navigate interface that simplifies the image compression process.
  • Multiple Formats Support
    Squoosh supports a wide range of image formats including JPEG, PNG, WebP, and AVIF, allowing for versatile usage.
  • Real-Time Comparison
    Users can compare the original and compressed images side-by-side in real time, providing immediate visual feedback on the compression quality.
  • Customization Options
    The app allows users to adjust various parameters such as quality, resizing, and other advanced settings for greater control over the compression.
  • Open Source
    Squoosh is an open-source project, meaning that its code is transparent and can be reviewed, modified, and improved by the community.
  • Offline Capability
    The application can also be used offline, adding a layer of convenience for users who may not always have consistent internet access.

Possible disadvantages of Squoosh

  • Limited Advanced Features
    While great for basic compression tasks, Squoosh might lack some advanced features found in professional image editing software.
  • File Size Limits
    There might be limitations on the size of the files that can be uploaded and processed, which could be a constraint for users dealing with very large images.
  • Web-Based Dependency
    As a web application, its performance can be influenced by the browser and device capability, which could vary significantly among users.
  • No Batch Processing
    Squoosh is designed for single-image processing. Users looking to compress multiple images at once will find this feature lacking.
  • Privacy Concerns
    Although it can be used offline, the nature of a web app raises concerns for users who prioritize privacy and data security.
  • Limited Support Resources
    Being a free tool, it doesn't come with professional support, so users might have to rely on community forums or documentation for help.

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 Squoosh

Overall verdict

  • Squoosh is an excellent tool for anyone needing quick and efficient image compression. Its flexibility and privacy-focused approach make it particularly appealing. Overall, it provides a seamless experience with effective results.

Why this product is good

  • Squoosh is a versatile image compression tool that supports various formats including WebP, PNG, and JPEG. It's known for its ease of use, allowing users to compress images directly in the browser without needing to upload files to a server, thus ensuring privacy. The user interface is intuitive, providing real-time previews of compression results, and it offers advanced options for adjusting quality settings to achieve the desired balance between image quality and file size.

Recommended for

    Web developers, designers, bloggers, and anyone needing to optimize images for the web, particularly those concerned about maintaining image quality while reducing file size.

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.

Squoosh videos

+ Add

Jumbo Squoosh-oโ€™s Review! #SLIMESTAGRAM #JumboSquooshos

More videos:

  • Review - DIY Stress Balls | *NEW* Galaxy Squoosh-O's Unboxing & Review!! | Sneak Peek
  • Review - Jumbo Squoosh-O's DIY Stress Toy Kit: Unboxing, Setup & 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 Squoosh and Plotly)

Squoosh

Plotly

Image Editing
100 100%
Image Editing
0% 0
Data Visualization
0 0%
Data Visualization
100% 100
Image Optimisation
100 100%
Image Optimisation
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 Squoosh and Plotly

Squoosh Reviews

  1. nathnolt
    Best tool to make images smaller or to figure out the right setting for batch work

    The only negative thing about this web app, is that it's not clear which formats are supported in which browsers.

    ๐Ÿ‘ Pros:    Intuitive|Easy user interface|User-friendly|Great user experience|Web app|Offline mode|Fast ui|Fast

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 thatโ€™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, Squoosh should be more popular than Plotly. It has been mentiond 200 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.

Squoosh mentions (200)

  • Can you build a recognizable World Map in under 500 bytes?
    Its a fun challenge. I used https://squoosh.app to make a pretty good one. Mostly just a resize and then OxiPNG for compression. Managed a 124x62 black/white image. OP has a resolution of 195x53, so I had very similar, but slightly worse I think? Mostly a different aspect ratio + map projection I think. Playing with Squoosh.app is very fun, and you can very easily see how the jump from 500b to ~1.5kb turns a map... - Source: Hacker News / about 1 month ago
  • Speed Up Your WordPress Site in 30 Minutes: A No-Plugin Performance Guide
    Use a free tool like Squoosh (by Google) to batch convert your existing images to WebP. - Source: dev.to / 3 months ago
  • Free Browser Tools for Developers Who Make Content
    Every image goes through Squoosh before it lands in any repo I own. Drag the file in, pick WebP or AVIF, drag the quality slider until the preview still looks clean, download. The size reduction is usually 60โ€“80% with no visible quality loss. It runs entirely locally in your browser โ€” nothing is uploaded anywhere. For a performance-conscious developer this matters. Best for: Pre-commit image optimisation, blog... - Source: dev.to / 4 months ago
  • Rust WASM vs TypeScript Performance: Why the 'Faster' Language Lost by 25% [2026]
    The Squoosh image compression app from Google is a great example. It runs codecs like MozJPEG and WebP entirely in WASM, processing large image buffers with minimal boundary crossings. Near-native compression performance, right in the browser. - Source: dev.to / 5 months ago
  • Flutter App Taking Too Long to Start? Here's What You're Doing Wrong
    For images, tools like TinyPNG or Squoosh can reduce file sizes dramatically, often by 60-80%, with little to no visible quality difference. For your splash screen specifically, consider using a simple vector image (SVG) or even a plain color with your logo instead of a heavy raster image. Flutter's native splash screen supports this out of the box and it's blazing fast. - Source: dev.to / 6 months 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 / 5 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!๐Ÿค“
    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 / over 1 year 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 Squoosh and Plotly, you can also consider the following products

TinyPNG - Make your website faster and save bandwidth. TinyPNG optimizes your PNG images by 50-80% while preserving full transparency!

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.

iLoveIMG - iLoveIMG is one of most powerful solution that comes with all the major tool you cloud want to edit images in bulk.

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

Caesium Image Compressor - Compress your pictures up to 90% without visible quality loss.

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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