Software Alternatives, Accelerators & Startups

kops VS Plotly

Compare kops VS Plotly and see what are their differences

kops logo kops

Founded by Elsa Kopp in 1950, Kopp's Frozen Custard specializes in Milwaukee's best freshly made frozen custard and jumbo burgers.

Plotly logo Plotly

Low-Code Data Apps
  • kops Landing page
    Landing page //
    2023-05-23
  • Plotly Landing page
    Landing page //
    2023-07-31

kops features and specs

  • Ease of Use
    Kops provides a user-friendly interface and automates many of the complex tasks involved in setting up a Kubernetes cluster, making it accessible for users with varying levels of expertise.
  • Cloud Provider Support
    Kops is designed to work seamlessly with AWS, which is its primary target environment. It also supports other cloud providers, though AWS is where it is most mature and feature-complete.
  • Customizability
    Kops allows a high degree of customization for your cluster configurations, including networking, security, and machine types, enabling you to tailor the setup according to your specific needs.
  • Open Source
    Kops is open-source software, which means it benefits from community contributions and improvements, and you have the freedom to inspect, modify, and share your own versions of the software.
  • Integrated with Kubernetes Practices
    Kops encourages and supports best practices for Kubernetes deployments, ensuring that the clusters are set up following industry standards for security and reliability.

Possible disadvantages of kops

  • Limited Multi-Cloud Support
    While Kops has some support for multiple cloud providers, it is primarily focused on AWS. Users requiring robust multi-cloud support might find Kops limiting compared to other solutions.
  • Complexity
    For very simple or small-scale clusters, Kops might introduce unnecessary complexity, with its multitude of features and configurations that are designed for more robust setups.
  • Resource Intensive
    Running Kops, especially in larger environments, can be resource-intensive, requiring a significant amount of upfront and ongoing cloud resources, which might not be cost-effective for smaller workloads.
  • Learning Curve
    Despite its automation capabilities, there is still a learning curve associated with effectively using Kops, especially for users who are not already familiar with Kubernetes concepts.
  • Dependency on Cloud Features
    Kops requires certain cloud-specific features, especially in AWS, which can lead to vendor lock-in if you're heavily invested in these features for your Kubernetes deployment.

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.

kops videos

Kops potato head review

More videos:

  • Review - Setup Kubernetes on AWS | Kubernetes Cluster on AWS Using Kops | Kubernetes AWS Kops

Plotly videos

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 kops and Plotly)
Developer Tools
100 100%
0% 0
Data Visualization
0 0%
100% 100
Cloud Computing
100 100%
0% 0
Data Dashboard
0 0%
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 kops and Plotly

kops Reviews

We have no reviews of kops 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.
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...
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.

Social recommendations and mentions

Based on our record, Plotly seems to be more popular. 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.

kops mentions (0)

We have not tracked any mentions of kops yet. Tracking of kops recommendations started around Mar 2021.

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 / about 1 month 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 / 3 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 / 5 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 / 11 months 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
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What are some alternatives?

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

Kontena Lens - Kontena Lens is an open-source desktop application that comes with a reliable way to manage and monitor Kubernetes clusters.

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.

Rancher - Open Source Platform for Running a Private Container Service

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

minikube - Run Kubernetes locally. Contribute to kubernetes/minikube development by creating an account on GitHub.

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