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LogicMonitor VS Matplotlib

Compare LogicMonitor VS Matplotlib and see what are their differences

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LogicMonitor logo LogicMonitor

LogicMonitor is the SaaS performance monitoring platform for the world's best IT teams. Deploy Fast, Monitor More, Improve Ops.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • LogicMonitor Landing page
    Landing page //
    2023-10-18
  • Matplotlib Landing page
    Landing page //
    2023-06-14

LogicMonitor features and specs

  • Comprehensive Monitoring
    LogicMonitor provides end-to-end IT infrastructure monitoring, including servers, networks, applications, and cloud services, ensuring holistic visibility.
  • Scalability
    Designed to handle both small and large enterprises, LogicMonitor can scale effortlessly with the growth of an organization’s IT infrastructure.
  • Ease of Deployment
    The platform is known for its quick setup process, allowing businesses to deploy and gain insights rapidly without significant downtime.
  • Customizable Dashboards
    Offers highly customizable dashboards that allow users to visualize data and metrics in a manner that suits their specific needs.
  • Automated Discovery
    Automatically discovers devices and applications within the network, significantly reducing the manual effort required for setup.
  • Third-party Integrations
    Supports numerous third-party integrations, enhancing its capabilities and making it easier to fit into an existing tech ecosystem.
  • Real-time Alerting
    Features real-time alerting mechanisms that help IT teams respond swiftly to potential issues, minimizing downtime and disruption.
  • Cloud and Hybrid Environment Support
    Offers robust support for cloud-based and hybrid environments, making it suitable for modern infrastructures that leverage diverse technologies.

Possible disadvantages of LogicMonitor

  • Cost
    Potentially high costs can be prohibitive for smaller organizations, particularly when additional features or large-scale deployments are involved.
  • Complexity
    Although powerful, the platform can be complex and may require a steep learning curve for users not familiar with advanced monitoring tools.
  • Resource Intensive
    The software can be resource-intensive, potentially necessitating additional hardware or computing resources to operate efficiently.
  • Customization Limitations
    Despite offering customization, certain areas may feel limited, especially for organizations with highly specific monitoring needs.
  • Dependency on Internet Connectivity
    Being a SaaS solution, LogicMonitor requires a reliable internet connection; any disruptions in connectivity can impact monitoring capabilities.
  • Alert Spam
    Without proper configuration, users might experience alert fatigue due to an overwhelming number of notifications.
  • Support Limitations
    While support is generally strong, some users report delays or less than satisfactory resolutions during peak times or with complex issues.

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 LogicMonitor

Overall verdict

  • Yes, LogicMonitor is generally considered a good monitoring solution.

Why this product is good

  • LogicMonitor is praised for its comprehensive monitoring capabilities, ease of use, and scalability. It supports a wide range of technologies and offers robust reporting and alerting features. Users appreciate its cloud-based nature, which allows for quick deployment and minimal maintenance.

Recommended for

  • IT teams looking for a scalable, cloud-based monitoring solution.
  • Organizations seeking a tool with strong reporting and alerting capabilities.
  • Businesses that need to monitor a wide array of technologies and devices.

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.

LogicMonitor videos

+ Add

An Introduction to LogicMonitor

More videos:

  • Review - Step Inside LogicMonitor [OUTDATED 2/4/20]
  • Review - Ted Baker Customer Fireside Chat | LogicMonitor Level Up Event June 2019

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to LogicMonitor and Matplotlib)

LogicMonitor

Matplotlib

Monitoring Tools
100 100%
Monitoring Tools
0% 0
Technical Computing
0 0%
Technical Computing
100% 100
Log Management
100 100%
Log Management
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
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 LogicMonitor and Matplotlib

LogicMonitor Reviews

Top 10 PRTG Alternatives for Monitoring Networks and IT Infrastructure
If you’re not looking to be overwhelmed with network alerts, consider using LogicMonitor to automatically identify and take action for the most important alerts with 90% less noise.
Source: www.networkstraining.com
7 Best Containerization Software Solutions of 2022
LogicMonitor’s dynamic topology mapping feature provides an at-a-glance view of your entire infrastructure, including networks, servers, containers, and more.
Source: techgumb.com
8 Dynatrace Alternatives to Consider in 2021
LogicMonitor is a massive proponent of hybrid IT. It is extensible and secure infrastructure monitoring on a single platform. With over 2,000 integrations available, it is a powerful package with many features that support configuration monitoring and AIOps early warning systems.
Source: scoutapm.com
Best New Relic Alternatives for Application Performance Monitoring (Cloud & SaaS)
Their Auto-Discover feature scans your systems and pulls data and information into easy to read graphs and data points that help you manage and monitor pain points. LogicMonitor helps you be more proactive about monitoring mission critical systems and lets you look at historical data to plan for future growth and capacity planning.
Source: www.ittsystems.com
15 Best IT Monitoring Tools and Software
LogicMonitor offers monitoring templates and frequently expands to include new features that increase its functionality.
Source: blog.inedo.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 doesn’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 more popular. It has been mentiond 107 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.

LogicMonitor mentions (0)

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

Matplotlib mentions (107)

  • Python for Data Visualization: Best Tools and Practices
    Matplotlib is the backbone of Python data visualization. It’s a flexible, reliable library for creating static plots. Whether you're making simple bar charts or complex graphs, Matplotlib allows extensive customization. You can adjust nearly every aspect of a plot to suit your needs. - Source: dev.to / 2 months ago
  • Build a Competitive Intelligence Tool Powered by AI
    Add data visualization to make it actionable for your business using pandas.pydata.org and matplotlib.org. - Source: dev.to / 6 months ago
  • Data Visualisation Basics
    Matplotlib: a versatile library for visualizations, but it can take some code effort to put together common visualizations. - Source: dev.to / 9 months ago
  • Creating a CSV to Graph Generator App Using ToolJet and Python Libraries
    In this tutorial, we'll create a CSV to Graph Generator app using ToolJet and Python code. This app enables users to upload a CSV file and generate various types of graphs, including line, scatter, bar, histogram, and box plots. Since ToolJet supports Python (and JavaScript) code out of the box, we'll incorporate Python code and the matplotlib library to handle the graph generation. Additionally, we'll use... - Source: dev.to / 10 months ago
  • Something is strange with CrowdStrike timeline
    It looks like matplotlib to me: https://matplotlib.org/. - Source: Hacker News / 10 months ago
View more

What are some alternatives?

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

Dynatrace - Cloud-based quality testing, performance monitoring and analytics for mobile apps and websites. Get started with Keynote today!

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

Datadog - See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.

GnuPlot - Gnuplot is a portable command-line driven interactive data and function plotting utility.

Zabbix - Track, record, alert and visualize performance and availability of IT resources

Plotly - Low-Code Data Apps

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