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Supabase UI VS Plotly

Compare Supabase UI 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

Supabase UI logo Supabase UI

React component library for enterprise dashboards

Plotly logo Plotly

Low-Code Data Apps
  • Supabase UI Landing page
    Landing page //
    2022-04-08
  • Plotly Landing page
    Landing page //
    2023-07-31

Supabase UI features and specs

  • Ease of Integration
    Supabase UI components are designed to integrate seamlessly with Supabase projects, making it easier for developers to add user interface elements without extensive setup or configuration.
  • Customizability
    Supabase UI offers customizable components that can be tailored to fit the unique design requirements of various projects, allowing for greater flexibility in UI design.
  • Consistency
    Using Supabase UI ensures a consistent look and feel across applications that rely on Supabase, facilitating a unified user experience.
  • Open Source
    Supabase UI is open source, meaning developers can view, modify, and contribute to the source code, fostering community involvement and transparency.

Possible disadvantages of Supabase UI

  • Limited Component Library
    Compared to more established UI libraries, Supabase UI may have a smaller set of available components, which may not cover all use cases.
  • Early Development Stage
    As a newer solution, Supabase UI might experience rapid changes and updates, possibly leading to instability or breaking changes in some releases.
  • Dependency on Supabase
    While tailored for Supabase, this tight integration may make it less ideal for projects that do not use Supabase as their backend solution.
  • Potential Learning Curve
    Developers who are not familiar with Supabase or its ecosystem might face a learning curve when trying to understand and use the UI components effectively.

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 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.

Supabase UI videos

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

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Plotly videos

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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 Supabase UI and Plotly)

Supabase UI

Plotly

Developer Tools
100 100%
Developer Tools
0% 0
Data Visualization
0 0%
Data Visualization
100% 100
Design Tools
100 100%
Design 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 Supabase UI and Plotly

Supabase UI Reviews

We have no reviews of Supabase UI yet.
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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, Plotly should be more popular than Supabase UI. It has been mentiond 34 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.

Supabase UI mentions (5)

  • Supabase UI: Platform Kit
    The library is 100% shadcn/ui compatible by leveraging the component registry feature. Components are styled with shadcn/ui and Tailwind CSS and are completely customizable. Read the original launch post for more details, or check out the docs: ui.supabase.com. - Source: dev.to / 12 months ago
  • Frontend letter to frontend lovers
    Supabase have introduced new Supabase UI, just like we did iHateReading UI ๐Ÿ˜ƒ. - Source: dev.to / about 1 year ago
  • Supabase adoption guide: Overview, examples, and alternatives
    Supabase UI is an open source library of UI components that was inspired by Tailwind and Ant Design and seeks to help developers quickly build applications with Supabase. This library provides a set of pre-built components that are styled and ready to use, ensuring consistency and reducing the amount of time needed to develop the UI. - Source: dev.to / almost 2 years ago
  • User Authentication in Next.js with Supabase
    Supabase also provides an open source component library called Supabase UI, which is a collection of common UI components and utilities that are used across the range of Supabase products. Its styling is heavily inspired by Tailwind CSS, so you know it will look good out of the box. - Source: dev.to / over 4 years ago
  • The Open Source alternative to Twilio (Fonoster) is the second most popular repo in GitHub today for the Javascript category
    Nothing to do with Superbase. But because the logo is green I decided to use their site as the base for mine. No to mention that we are early adopters of https://ui.supabase.io/ (hoping they add theming soon). Source: over 4 years ago

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 / 4 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
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What are some alternatives?

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

NextUI - NextUI is the next-gen UI React library that allows you to make beautiful websites regardless of your design experience, comes with awesome features like Auto Dark Mode recognition, Themes support, easy customization, Best-in-class DX and much more.

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.

Supabase - An open source Firebase alternative

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

Flawwwless ui - Simplified open source React.js components library ๐Ÿš€

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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