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Javalin VS Plotly

Compare Javalin VS Plotly and see what are their differences

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Javalin logo Javalin

Simple REST APIs for Java and Kotlin

Plotly logo Plotly

Low-Code Data Apps
  • Javalin Landing page
    Landing page //
    2022-10-26
  • Plotly Landing page
    Landing page //
    2023-07-31

Javalin features and specs

  • Lightweight
    Javalin is a lightweight framework with minimal dependencies, making it easy to integrate into existing projects and reducing overhead.
  • Simplicity
    The framework is simple to use and has a straightforward API, which makes it easier for developers to understand and work with.
  • Kotlin & Java Support
    Javalin natively supports both Kotlin and Java, making it flexible for projects written in either language.
  • WebSocket Support
    It includes built-in support for WebSockets, enabling real-time communication between the client and server without additional dependencies.
  • Extensive Documentation
    Javalin comes with comprehensive documentation and guides, which help developers get up to speed quickly.

Possible disadvantages of Javalin

  • Limited Features
    As a minimalist framework, Javalin may lack some advanced features present in more comprehensive frameworks, requiring additional implementations from developers.
  • Community Support
    While growing, the community around Javalin is not as large as other established frameworks, which may result in fewer resources or third-party libraries.
  • Performance Overhead
    Though lightweight, Javalin may not offer the same level of performance optimization as frameworks specifically designed for high-performance use cases.
  • Limited Middleware
    Compared to other frameworks, the middleware support in Javalin is more limited, potentially requiring additional code for customization.

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.

Javalin videos

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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 Javalin and Plotly)

Javalin

Plotly

Web Frameworks
100 100%
Web Frameworks
0% 0
Data Visualization
0 0%
Data Visualization
100% 100
Developer Tools
100 100%
Developer 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 Javalin and Plotly

Javalin Reviews

We have no reviews of Javalin 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

Javalin might be a bit more popular than Plotly. We know about 37 links to it since March 2021 and only 34 links to Plotly. 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.

Javalin mentions (37)

  • Java 26 Is Here, and with It a Solid Foundation for the Future
    Helidon SE (https://helidon.io/#se) or Javalin (https://javalin.io/) would be more in that vein - straight-forward modern Java, super fast. - Source: Hacker News / 6 months ago
  • Year After Switching from Java to Go: Our Experiences
    But Javas has so many of these web frameworks?! * Spring (https://spring.io/) * Spring Boot (https://spring.io/projects/spring-boot) * Helidon (https://helidon.io/) * Micronaut (https://micronaut.io/) * Quarkus (https://quarkus.io/) * JHipster (https://www.jhipster.tech/) * Vaadin (https://vaadin.com/) That's just to mention the bigger ones, there's lots of mini frameworks like Javalin (https://javalin.io/) and... - Source: Hacker News / over 1 year ago
  • Latudio – a language acquisition app with a listening-oriented approach
    - like Sentences exercise, but you can select your own set of sentences. You can also set goals and view statistics about your progress. None of this would be possible without the great help from hundreds of our contributors [3], who translated, mapped and recorded content. All the content you find in the app was reviewed multiple times by several people and recordings are made by native speakers. No story in the... - Source: Hacker News / almost 2 years ago
  • Show HN: Donobu – Mac App for Web Automation and Testing
    - Javalin 6 for the web framework (https://javalin.io/). - Source: Hacker News / almost 2 years ago
  • Spark – A web micro framework for Java and Kotlin
    I'd recommend Javalin (https://javalin.io/) instead. Same idea, only executed better and it is actively maintained. - Source: Hacker News / over 2 years 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 / 6 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 / almost 2 years 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 Javalin and Plotly, you can also consider the following products

vert.x - From Wikipedia, the free encyclopedia

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.

Micronaut Framework - Build modular easily testable microservice & serverless apps

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

Spark Framework - Spark Framework is a simple and lightweight Java web framework built for rapid development.

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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