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Plotly VS Stacker

Compare Plotly VS Stacker and see what are their differences

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Plotly logo Plotly

Low-Code Data Apps

Stacker logo Stacker

No-Code internal tools powered by Airtable, GSheets + more
  • Plotly Landing page
    Landing page //
    2023-07-31
  • Stacker Landing page
    Landing page //
    2023-06-28

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.

Stacker features and specs

  • User-Friendly Interface
    Stacker provides a highly intuitive drag-and-drop interface, making it accessible for users with little to no technical expertise to create custom business applications.
  • Integration Capabilities
    It offers seamless integration with popular platforms like Airtable, Google Sheets, and Salesforce, allowing users to consolidate data from multiple sources into a single platform.
  • Customization Options
    Stacker allows for significant customization of workflows, views, and permissions, enabling businesses to tailor the platform to their specific needs.
  • Rapid Development
    Businesses can quickly develop and deploy applications, reducing the time to market for new solutions and improving overall efficiency.
  • Collaboration Features
    Enhanced collaboration tools allow team members to share and manage data easily, boosting productivity and ensuring everyone is on the same page.
  • Scalability
    The platform can scale with your business, supporting a growing number of users and increasingly complex data needs.

Possible disadvantages of Stacker

  • Cost
    Stacker can be relatively expensive for small businesses or startups, particularly if they require advanced features or larger user bases.
  • Learning Curve
    Despite its user-friendly interface, there can still be a learning curve for new users, especially when it comes to understanding all the customization options and optimal use cases.
  • Customer Support
    Some users have reported that customer support can be slow to respond or not as helpful as needed, which can be a drawback if you encounter issues.
  • Limited Offline Access
    The platform relies heavily on internet connectivity, which can be a limitation for users who need offline access to their applications.
  • Feature Limitations
    While Stacker provides a wide range of features, it may not have all the advanced functionalities that some highly specialized industries require.

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.

Analysis of Stacker

Overall verdict

  • Stacker is a good option for teams looking to leverage their existing data infrastructure to create functional applications without investing heavily in software development resources. It is particularly beneficial for companies looking to improve operational efficiencies quickly and cost-effectively.

Why this product is good

  • Stacker is a no-code platform that allows businesses and teams to build custom apps using their existing data sources like Google Sheets, Airtable, and others. It is praised for its user-friendly interface, enabling non-technical users to create applications without the need for traditional coding. It enhances productivity by streamlining workflows and is customizable to fit various business needs.

Recommended for

  • Small to medium-sized businesses looking to automate tasks.
  • Teams seeking to create custom applications without code.
  • Organizations already using data tools like Airtable or Google Sheets.
  • Non-technical users who want to build apps without developer help.

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

Stacker videos

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

Add video

Category Popularity

0-100% (relative to Plotly and Stacker)

Plotly

Stacker

Data Visualization
100 100%
Data Visualization
0% 0
No Code
0 0%
No Code
100% 100
Data Dashboard
100 100%
Data Dashboard
0% 0
Productivity
0 0%
Productivity
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 Stacker

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

Stacker Reviews

The best no-code tools for sales teams
You can create an app in minutes. Thanks to Stacker’s handy template library, you can create your app in practically no time at all. Simply plug in your existing data sources and your app will be up and running in a few clicks. Of course, there’s also the option to build it from scratch.
Source: www.nocode.tech

Social recommendations and mentions

Based on our record, Plotly should be more popular than Stacker. 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 / 7 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 / about 1 year 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

Stacker mentions (7)

View more

What are some alternatives?

When comparing Plotly and Stacker, 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.

Retool - Build custom internal tools in minutes.

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

ToolJet - Open-source alternative for Retool

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

NoCode.tech - Free tools & resources for non-tech makers and entrepreneurs

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