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Ajenti VS Matplotlib

Compare Ajenti VS Matplotlib and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Ajenti logo Ajenti

Web administration panel for servers and custom hardware

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • Ajenti Landing page
    Landing page //
    2018-10-02
  • Matplotlib Landing page
    Landing page //
    2023-06-14

Ajenti features and specs

  • User-Friendly Interface
    Ajenti offers a clean and intuitive user interface, making it easy for administrators to manage their servers without extensive technical knowledge.
  • Lightweight
    Ajenti is a relatively lightweight control panel, which means it won't consume significant system resources, allowing your server to maintain optimal performance.
  • Modular Architecture
    Ajenti features a modular architecture, which allows for easy extension and customization through various plugins to meet specific needs.
  • Built-in Terminal
    Ajenti includes a built-in terminal, which allows administrators to execute shell commands directly from the web interface, facilitating quicker management tasks.
  • Cross-Platform Compatibility
    Ajenti supports multiple operating systems, including Linux and BSD variants, making it a versatile choice for different server environments.
  • Open-Source
    Ajenti is open-source software, providing transparency, potential for community contributions, and cost savings compared to commercial solutions.

Possible disadvantages of Ajenti

  • Limited Community Support
    Despite being open-source, Ajenti has a smaller community compared to some other control panels, which can limit available resources and support options.
  • Fewer Integrated Services
    Ajenti may have fewer built-in modules or integrated services compared to more established control panels like cPanel or Plesk, requiring more manual setup.
  • Security Concerns
    As with any web-based control panel, Ajenti can present security risks if not properly configured and updated, potentially exposing the server to vulnerabilities.
  • Documentation Gaps
    The documentation for Ajenti might not be as comprehensive or up-to-date as needed, which can pose challenges for new users or those encountering specific issues.
  • Performance Limitations
    While lightweight, Ajenti's performance can be limited on high-traffic or resource-intensive servers, where more robust solutions might be more appropriate.

Matplotlib features and specs

  • Versatility
    Matplotlib can generate a wide variety of plots, ranging from simple line plots to complex 3D plots. This versatility makes it a go-to library for many scientific and technical visualizations.
  • Customization
    It offers extensive customization options for virtually every element of a plot, including colors, labels, line styles, and more, allowing users to tailor plots to meet specific needs.
  • Integrations
    Matplotlib integrates well with other Python libraries such as NumPy, Pandas, and SciPy, making it easier to plot data directly from these sources.
  • Community and Documentation
    It has a large, active community and comprehensive documentation that includes tutorials, examples, and detailed references, which can help users solve problems and improve their plot-making skills.
  • Interactivity
    Matplotlib supports interactive plots, which can be embedded in Jupyter notebooks and GUIs, allowing for dynamic data exploration and presentation.
  • Publication-Quality
    The library is capable of producing high-quality, publication-ready graphics that meet the stringent requirements of academic journals and professional presentations.

Possible disadvantages of Matplotlib

  • Complexity
    While Matplotlib offers extensive customization, it can be complex and sometimes unintuitive for beginners, requiring a steep learning curve to master all its functionality.
  • Performance
    Rendering a large number of plots or handling very large datasets can be slow, making Matplotlib less suitable for real-time data visualization.
  • Modern Aesthetics
    Out-of-the-box plots from Matplotlib can look somewhat dated compared to those from newer plotting libraries like Seaborn or Plotly, requiring additional customization to achieve a modern look.
  • 3D Plots
    Although Matplotlib supports 3D plotting, its capabilities are relatively limited and less sophisticated compared to specialized 3D plotting libraries.
  • Size and Structure
    The package is relatively large and can be slow to import. Its extensive structure can make finding specific functions and understanding the overall architecture challenging.

Analysis of Ajenti

Overall verdict

  • Ajenti is generally regarded as a good choice, especially for smaller teams or individual users who need a straightforward and efficient way to manage servers without delving deep into technical complexities.

Why this product is good

  • Ajenti is considered a good option for its ease of use, extensibility, and comprehensive feature set for server management. It provides a user-friendly, web-based interface that simplifies tasks like monitoring system performance, managing services, and editing configuration files without needing advanced Linux command-line knowledge. Additionally, the platform supports plugins, allowing users to customize and extend its functionalities to better suit their specific needs.

Recommended for

  • System administrators looking for a user-friendly interface to manage Linux servers.
  • Developers who need a lightweight and flexible control panel for development environments.
  • Small to medium-sized businesses that require a cost-effective solution for managing server infrastructure.

Analysis of Matplotlib

Overall verdict

  • Yes, Matplotlib is a good library for data visualization, particularly for users who require a versatile and powerful plotting solution in Python.

Why this product is good

  • Matplotlib is highly regarded due to its extensive customization options, versatility in creating a wide range of static, animated, and interactive plots, and its large user community and support. It integrates well with other scientific libraries in Python, making it a staple for data visualization. The library is also open-source and frequently updated, ensuring it remains a reliable choice for users.

Recommended for

  • Data scientists and analysts needing to create detailed, customized visual representations of their data.
  • Researchers and engineers looking for a comprehensive plotting library that supports scientific and engineering formats.
  • Python developers who require integration with other scientific computing libraries like NumPy and Pandas.

Ajenti videos

+ Add

How to Install Ajenti for Managing Linux Server

More videos:

  • Tutorial - Part 18 :: Set up and use Ajenti - Digital Ocean Tutorials
  • Tutorial - how to install #ajenti cPanel centos 7

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to Ajenti and Matplotlib)

Ajenti

Matplotlib

Hosting
100 100%
Hosting
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Control Panels
100 100%
Control Panels
0% 0
Technical Computing
0 0%
Technical Computing
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 Ajenti and Matplotlib

Ajenti Reviews

Top 12 Best VPS Control Panels for 2025
Ajenti is available for free. However, there is a commercial license available if you want to use it on multiple servers. Installing Ajenti is relatively painless, thanks to a packaging script.
Source: blog.radwebhosting.com
Explore Top VestaCP Alternative: Find the Perfect Control Panel for Your Hosting Needs
Ajenti stands as an exceptional open-source control panel and administration tool, meticulously crafted to simplify the oversight of server infrastructure and applications through an intuitive web-based interface. Operating as a central command center, this platform adeptly consolidates the configuration of a wide array of server components, encompassing system settings,...
Source: cyberpanel.net
10 Most Popular Free Web Hosting Control Panels You Need To Know
Ajenti control panel for Linux and BSD servers and it is a free and open-source . Ajenti source is written in Python and uses the Gevent event loop for high performance. It is also highly modular, with a plug-in architecture that allows users to extend its functionality.
Source: www.techtransit.org
10 Best cPanel Alternatives and Competitors in 2022 and Beyond
Ajenti is a lightweight admin panel with fast remote access to everything. You wonโ€™t have to look for PuTTY downloads and can access the panel from anywhere.
Source: macpost.net
Top cPanel Alternatives worth trying in 2022
โ€œAn administration tool for a more civilized ageโ€ฆโ€?Ajenti truly stands by its words like a fast, secure, and highly recommended manager of a Linux system that you can use as a text editor. file manager, a terminal or something else. In fact, thereโ€™s more you can do. You can install packages, manage users, and even monitor resources with the ease you are expecting.
Source: vashishthakapoor.com

Matplotlib Reviews

25 Python Frameworks to Master
Matplotlib is a widely used tool for data visualization in Python. It provides an object-oriented API for embedding plots into applications.
Source: kinsta.com
5 Best Python Libraries For Data Visualization in 2023
You can use this library for multiple purposes such as generating plots, bar charts, histograms, power spectra, stemplots, pie charts, and more. The best thing about Matplotlib is you just have to write a few lines of code and it handles the rest by itself. Metaplotilib focuses on static images for publication along with interactive figures using toolkits like Qt and GTK.
Source: www.technotification.com
15 data science tools to consider using in 2021
Matplotlib is an open source Python plotting library that's used to read, import and visualize data in analytics applications. Data scientists and other users can create static, animated and interactive data visualizations with Matplotlib, using it in Python scripts, the Python and IPython shells, Jupyter Notebook, web application servers and various GUI toolkits.
Source: searchbusinessanalytics.techtarget.com
Top Python Libraries For Image Processing In 2021
Matplotlib is primarily used for 2D visualizations such as scatter plots, bar graphs, histograms, and many more, but we can also use it for image processing. It is effective to get information out of an image. It doesnโ€™t support all file formats.
Source: www.analyticsvidhya.com
Top 8 Python Libraries for Data Visualization
Matplotlib is a data visualization library and 2-D plotting library of Python It was initially released in 2003 and it is the most popular and widely-used plotting library in the Python community. It comes with an interactive environment across multiple platforms. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application...
Source: www.geeksforgeeks.org

Social recommendations and mentions

Based on our record, Matplotlib seems to be a lot more popular than Ajenti. While we know about 114 links to Matplotlib, we've tracked only 1 mention of Ajenti. 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.

Ajenti mentions (1)

  • Is Ajenti a dead project?
    The site at https://ajenti.org is it now a dead project? Their support forum seems to show messages about 7 years old as current topics. Does anyone know? Source: over 2 years ago

Matplotlib mentions (114)

  • The soul file
    In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ€” the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 5 months ago
  • How to Analyze CSV Files with Python and Pandas
    Numbers are useful, but sometimes itโ€™s easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 8 months ago
  • libmalloc, jemalloc, tcmalloc, mimalloc - Exploring Different Memory Allocators
    We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 8 months ago
  • Building an AI Scoring Agent: Step-By-Step
    NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 months ago
  • Top 5 GitHub Repositories for Data Science in 2026
    The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโ€ฆ. - Source: dev.to / 10 months ago
View more

What are some alternatives?

When comparing Ajenti and Matplotlib, you can also consider the following products

cPanel - With its first-class support and rich feature set, cPanel & WHM has been the web hosting industry's most reliable, intuitive control panel since 1997.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Webmin - Webmin is a web-based interface for system administration for Unix.

NumPy - NumPy is the fundamental package for scientific computing with Python

Vesta Control Panel - โ€“ What I love about Vesta is that it's fast and easy to use

Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.

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