SST VS Plotly

Compare SST VS Plotly and see what are their differences

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Plotly

Low-Code Data Apps

Landing page //
2023-08-27

Landing page //
2023-07-31

SST

Website: github.com
Pricing URL: -

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Plotly

Website: plotly.com
Pricing URL: Official Plotly Pricing

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SST features and specs

Ease of Use
SST is designed to simplify the process of building serverless applications, providing developers with higher-level abstractions and tools that streamline development.
Integration with AWS
SST is well-integrated with AWS services, allowing developers to leverage the full power of AWS infrastructure while maintaining a focus on serverless architecture.
Live Lambda Development
SST supports live Lambda development, enabling developers to make real-time changes and see them reflected immediately without the need for lengthy deployment processes.
Infrastructure as Code
With SST, developers can define their infrastructure programmatically, which promotes version control, scalability, and collaboration among team members.
Flexibility
SST provides flexibility to developers, allowing them to use popular libraries and frameworks alongside serverless components, thus accommodating various use cases.

Possible disadvantages of SST

Learning Curve
Developers unfamiliar with SST and its abstractions may face a learning curve in understanding how to effectively use the toolkit and take full advantage of its features.
AWS Lock-in
As SST is tightly integrated with AWS services, it can lead to vendor lock-in, making it challenging for organizations to switch to other cloud providers in the future.
Complexity for Small Projects
For smaller projects, the overhead introduced by SST's abstractions and tooling might be unnecessary, adding complexity without significant benefits.
Dependency on Community Support
SST relies on community support for maintenance and feature development, which could pose a risk if the community's interest wanes or if support does not keep pace with AWS innovations.

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.

SST videos

+ Add

Performix sst review fat burner

Plotly videos

+ Add

Create Real-time Chart with Javascript | Plotly.js Tutorial

Category Popularity

0-100% (relative to SST and Plotly)

SST

Plotly

Developer Tools

100 100%

Developer Tools

0% 0

Data Visualization

0 0%

Data Visualization

100% 100

Open Source

100 100%

Open Source

0% 0

Charting Libraries

0 0%

Charting Libraries

100% 100

User comments

Share your experience with using SST and Plotly. For example, how are they different and which one is better?

Reviews

These are some of the external sources and on-site user reviews we've used to compare SST and Plotly

SST Reviews

We have no reviews of SST 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 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

Plotly might be a bit more popular than SST. We know about 34 links to it since March 2021 and only 31 links to SST. 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.

SST mentions (31)

Best/low maintenance devops toolchain for basic sass?
After researching all night, https://github.com/serverless-stack/sst seems like a good trade off between flexibility, simplicity and features. Source: over 3 years ago
Dynamodb design with Appsync
I use https://github.com/serverless-stack/serverless-stack — not the serverless project. This one is far better. Source: over 4 years ago
A magical AWS serverless developer experience
That said: SST is open source, so you could maybe somehow reimplement their debug stack which is the websockets magic + the Lambda shim in terraform to get it working... Source: over 4 years ago
Anti-Patterns to Avoid in Lambda Based Apps
If you are using CDK then check out SST: https://github.com/serverless-stack/serverless-stack It's based on CDK and has a great local development environment for Lambda. It allows you to set breakpoints and test it locally: https://serverless-stack.com/examples/how-to-debug-lambda-functions-with-visual-studio-code.html. - Source: Hacker News / over 4 years ago
Introducing Serverless Cloud: AWS Serverless Power for Back-Ends—Without the Complexity
I'll just plug what we built, SST: https://github.com/serverless-stack/serverless-stack. Source: almost 5 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!🤓
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

What are some alternatives?

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

Netlify - Build, deploy and host your static site or app with a drag and drop interface and automatic delpoys from GitHub or Bitbucket

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.

Coolify - An open-source, hassle-free, self-hostable Heroku & Netlify alternative.

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

Vercel - Vercel is the platform for frontend developers, providing the speed and reliability innovators need to create at the moment of inspiration.

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.