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LoadComplete VS Plotly

Compare LoadComplete VS Plotly and see what are their differences

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LoadComplete logo LoadComplete

The only load testing tool to record, replay, and test in real browsers at scale.

Plotly logo Plotly

Low-Code Data Apps
  • LoadComplete Landing page
    Landing page //
    2022-10-01
  • Plotly Landing page
    Landing page //
    2023-07-31

LoadComplete features and specs

  • Ease of Use
    LoadComplete offers an intuitive interface that allows users to easily set up and execute load tests without needing extensive technical knowledge.
  • Comprehensive Reporting
    The tool provides detailed reports and analytics, making it easier for users to understand performance metrics and identify bottlenecks.
  • Integration Capabilities
    LoadComplete integrates well with various CI/CD tools, enhancing its utility in automated testing environments.
  • Real Browser Testing
    It enables testing using real browsers, ensuring that load tests closely simulate real user interactions and provide more accurate performance data.

Possible disadvantages of LoadComplete

  • Cost
    The pricing of LoadComplete can be high for small organizations or individuals, potentially limiting its accessibility for budget-conscious users.
  • Resource Intensive
    Running extensive tests may require significant computing resources, which could impact other operations if not managed properly.
  • Learning Curve
    Despite its usability, some aspects of the tool might have a learning curve, especially for users unfamiliar with load testing concepts.
  • Limited Protocol Support
    Compared to some other load testing tools, LoadComplete may support fewer protocols, which could be a limitation for testing complex systems.

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 LoadComplete

Overall verdict

  • LoadComplete (LoadNinja) is a powerful and reliable tool for teams looking for a comprehensive, scalable solution to performance testing. It's especially beneficial for teams that require ease of use and the ability to quickly execute and iterate tests without deep technical expertise in testing frameworks.

Why this product is good

  • LoadComplete, or LoadNinja, is renowned for its user-friendly interface and robust performance testing capabilities. It allows testers to create and execute performance tests without extensive programming knowledge, making it accessible to various users. Its cloud-based infrastructure facilitates realistic load testing scenarios by simulating thousands of users without the need for significant hardware investments. Additionally, its integration capabilities with popular CI/CD tools streamline the testing process within modern development workflows. LoadComplete also provides detailed analytics and reporting, helping teams identify performance bottlenecks and optimize applications efficiently.

Recommended for

  • Development teams looking for seamless integration with existing CI/CD pipelines
  • QA teams seeking a user-friendly interface for performance testing
  • Organizations that need to conduct scalable cloud-based load testing
  • Businesses aiming to identify and resolve performance issues rapidly to improve user experience

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.

LoadComplete videos

+ Add

LoadComplete 101: Getting Started in LoadComplete | SmartBear Academy

More videos:

  • Review - Hello Yogurt Game Review 1080p Official LoadComplete
  • Review - Hello Yogurt Game Review 1080p Official LoadComplete

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

Category Popularity

0-100% (relative to LoadComplete and Plotly)

LoadComplete

Plotly

Website Testing
100 100%
Website Testing
0% 0
Data Visualization
0 0%
Data Visualization
100% 100
Load And Performance Testing
100 100%
Load And Performance Testing
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 LoadComplete and Plotly

LoadComplete Reviews

We have no reviews of LoadComplete 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

Based on our record, Plotly seems to be a lot more popular than LoadComplete. While we know about 34 links to Plotly, we've tracked only 1 mention of LoadComplete. 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.

LoadComplete mentions (1)

  • Automated Performance Testing?
    Browser Testing: Hit pages with virtual users performing a flow e.g. Sign up, login. If you want a report of how many "real" users can use your app concurrently, then this testing would give the closest "real" world statistics. Cons - price and requires JS/TS scripting knowledge. Tools: BrowserStorm, Flood.IO, LoadNinja. Source: over 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 / 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
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What are some alternatives?

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

WebLOAD - WebLOAD - The most flexible and cost effective software for enterprise load, stress and performance testing, integrated with DevOps processes. Click for details

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.

OctoPerf - OctoPerf is an enterprise-grade load testing platform, available as SaaS & on-premise, helping IT teams validate scalability at lower cost.

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

StresStimulus - Load testing tool for websites and mobile that works with hard-to-test applications.

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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