Software Alternatives, Accelerators & Startups

Plotly VS SHADERed

Compare Plotly VS SHADERed and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Plotly logo Plotly

Low-Code Data Apps

SHADERed logo SHADERed

Lightweight, full-featured desktop tool for creating and testing HLSL and GLSL shaders
  • Plotly Landing page
    Landing page //
    2023-07-31
  • SHADERed Landing page
    Landing page //
    2022-11-04

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.

SHADERed features and specs

  • Real-time Shader Editing
    SHADERed provides a real-time environment for shader development, allowing developers to see changes instantly as they edit code.
  • Cross-platform Compatibility
    The tool is compatible with Windows, macOS, and Linux, ensuring a broad range of developers can utilize SHADERed regardless of their operating system.
  • Support for Multiple Shader Types
    SHADERed supports a variety of shader types, including vertex, fragment, and compute shaders, providing flexibility in shader development.
  • Built-in Debugging Tools
    The application comes with debugging tools such as breakpoint support and a watch window, which are valuable for monitoring shader variables and debugging code.
  • Open Source
    Being open-source, SHADERed encourages community involvement and contributions, allowing anyone to suggest improvements or directly contribute to the tool's development.

Possible disadvantages of SHADERed

  • Steep Learning Curve
    New users, especially those unfamiliar with shader programming, may find SHADERed to have a steep learning curve due to its technical nature and extensive features.
  • Limited Documentation
    While the community may provide support, official documentation might be lacking or insufficient for some users, making it harder to fully understand all its features.
  • Potential Performance Issues
    As with many real-time applications, SHADERed can potentially consume significant system resources, which might lead to performance issues on lower-end hardware.
  • Complex User Interface
    The interface can be overwhelming for new users due to the multitude of features and options, hindering ease of use and user experience.
  • Niche Tool
    Being specifically geared towards shader editing, its use-case is niche, primarily appealing to developers who specifically need this functionality in their projects.

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.

Plotly videos

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

SHADERed videos

No SHADERed videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Plotly and SHADERed)
Data Visualization
100 100%
0% 0
3D
0 0%
100% 100
Data Dashboard
100 100%
0% 0
Interactive Exhibits
0 0%
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 Plotly and SHADERed

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.
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...
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.

SHADERed Reviews

We have no reviews of SHADERed yet.
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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.

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 / 6 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 / 12 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

SHADERed mentions (0)

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

What are some alternatives?

When comparing Plotly and SHADERed, 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.

Shadertoy - Build shaders, share them, and learn from the best community.

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

GLSL Sandbox - An online GSGL Shader Gallery and live development tool.

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

Shader Editor - Android app to create GLSL shaders and use them as live wallpaper