Software Alternatives, Accelerators & Startups

Dokku VS Plotly

Compare Dokku VS Plotly and see what are their differences

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Dokku logo Dokku

Docker powered mini-Heroku in around 100 lines of Bash

Plotly logo Plotly

Low-Code Data Apps
  • Dokku Homepage
    Homepage //
    2024-08-26
  • Dokku Landing page
    Landing page //
    2023-07-24
  • Plotly Landing page
    Landing page //
    2023-07-31

Dokku features and specs

  • Ease of Use
    Dokku provides simple commands and clear documentation, making it straightforward to deploy, manage, and scale applications using a process similar to Heroku.
  • Heroku Compatibility
    Dokku uses a Heroku-like buildpack system, which allows users to deploy applications with ease if they are already familiar with Heroku.
  • Cost-Effective
    Being an open-source project, Dokku itself is free to use, which can significantly reduce the cost of deploying applications compared to using premium services.
  • Customizability
    As an open-source tool, Dokku allows for extensive customization according to user needs, offering flexibility in deployment settings and configurations.
  • Plugin System
    Dokku supports a wide range of plugins, enabling users to extend its functionality easily, such as adding database support, monitoring capabilities, and more.

Possible disadvantages of Dokku

  • Initial Setup Complexity
    Setting up Dokku for the first time might be challenging, especially for users with limited experience in server management and Linux administration.
  • Limited Built-In Features
    Compared to fully-managed PaaS solutions, Dokku has fewer built-in features, potentially requiring more effort to implement certain functionalities such as load balancing and extensive monitoring.
  • Scalability Challenges
    While Dokku supports basic scaling, it might not handle extensive scaling needs as efficiently as more robust enterprise-level solutions.
  • Resource Management
    Dokku's resource management capabilities are limited compared to dedicated orchestration tools like Kubernetes, making it less suitable for complex and large-scale application deployments.
  • Community Support
    Even though Dokku has a growing community, it is not as large or as active as some of the more popular platforms, which can limit the availability of community-driven support and resources.

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 Dokku

Overall verdict

  • Dokku is a solid option for teams or developers looking for a cost-effective way to deploy and manage applications with the flexibility of a self-hosted solution. While it might not be as polished or feature-rich as commercial PaaS providers like Heroku or AWS Elastic Beanstalk, its open-source nature and community support make it a reliable choice for those who are comfortable with a bit more hands-on management.

Why this product is good

  • Dokku is often hailed as a self-hosted Platform as a Service (PaaS) solution, which is based on Docker. It simplifies the deployment process by allowing developers to manage applications similar to how they would on Heroku, but with more control and flexibility. Dokku is lightweight, can be scaled easily, and integrates well with various databases and programming languages. It is also open-source and can be installed on any server that supports Docker, making it a cost-effective solution for many projects.

Recommended for

  • Small to medium-sized projects
  • Developers who prefer open-source solutions
  • Teams looking for a Heroku-like experience on their own infrastructure
  • Cost-conscious developers or startups
  • Technical users who are comfortable managing their server environment

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.

Dokku videos

00028 Creating Your Own PaaS with Dokku

More videos:

  • Review - Dokku - An open source PAAS alternative to Heroku. You could save $$$ money!
  • Review - Rise Up and Deploy Your Own Heroku-like Service with Dokku in Minutes! #webdevelopment #tutorial

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 Dokku and Plotly)
Cloud Computing
100 100%
0% 0
Data Visualization
0 0%
100% 100
Cloud Hosting
100 100%
0% 0
Charting Libraries
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 Dokku and Plotly

Dokku Reviews

Heroku Free Tier Gone โ€” 10 Alternatives Still Free in April 2026
Dokku is an open-source Heroku clone you can run on any VPS. It supports Heroku buildpacks and gives you complete control. Requires server administration skills.
Source: snapdeploy.dev
35+ Of The Best CI/CD Tools: Organized By Category
Dokku is a great alternative if youโ€™re working with a stringent budget. Itโ€™s a miniaturized self-hosted platform as a service. You can deploy applications to it using Git. Because itโ€™s a Heroku derivative, itโ€™s compatible with Heroku apps.
Heroku vs self-hosted PaaS
CapRover is in many ways similar to Dokku. It uses Docker for deployment just like Dokku but CapRover does not support buildpack deployments as it uses Dockerfiles only. This is not necessarily a bad thing since Dockerfile deployments are great in Dokku as well. You donโ€™t have to write your own dockerfiles however for simple deployments as there are multiple defaults for...
Source: www.mskog.com

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 thatโ€™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

Plotly might be a bit more popular than Dokku. We know about 34 links to it since March 2021 and only 29 links to Dokku. 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.

Dokku mentions (29)

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 / 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!๐Ÿค“
    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
View more

What are some alternatives?

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

Google App Engine - A powerful platform to build web and mobile apps that scale automatically.

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.

Salesforce Platform - Salesforce Platform is a comprehensive PaaS solution that paves the way for the developers to test, build, and mitigate the issues in the cloud application before the final deployment.

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

Google Cloud Functions - A serverless platform for building event-based microservices.

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.