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NumPy VS Nagios

Compare NumPy VS Nagios and see what are their differences

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NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Nagios logo Nagios

Complete monitoring and alerting for servers, switches, applications, and services
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Nagios Landing page
    Landing page //
    2023-10-21

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

Nagios features and specs

  • Extensive Community Support
    Nagios has a large and active user community, which means you can easily find help and resources online. There are numerous plugins and add-ons developed by the community that can extend the functionality of Nagios.
  • Highly Customizable
    Nagios is highly customizable and flexible. It allows you to tailor monitoring to suit your specific needs, including creating custom plugins, modifying configuration files, and integrating with other tools.
  • Comprehensive Monitoring
    Nagios provides detailed monitoring of network services, host resources, and infrastructure systems. This includes the ability to monitor CPU load, disk usage, memory, and more.
  • Alerting and Notification
    Nagios has robust alerting and notification features that ensure you can stay informed of any issues or downtime. Alerts can be sent via email, SMS, or other communication channels.
  • Scalable
    Nagios is scalable and can grow with your organization. It supports a large number of hosts and services, making it suitable for both small and large enterprises.

Possible disadvantages of Nagios

  • Steep Learning Curve
    Nagios can be quite complex to set up and configure, especially for newcomers. The learning curve is steep, requiring time and effort to fully understand and utilize its capabilities.
  • Manual Configuration
    A significant amount of configuration is manual, particularly in the open-source version. This can be time-consuming and prone to human error, especially in larger environments.
  • Interface
    The user interface of Nagios is often considered outdated and less intuitive compared to other modern monitoring tools. The web interface can be difficult to navigate and is not as visually appealing.
  • Performance Issues
    Nagios can experience performance issues, particularly when monitoring a large number of hosts and services. It can become resource-intensive, requiring careful optimization and tuning.
  • Cost of Enterprise Version
    The enterprise version of Nagios, Nagios XI, comes with a significant cost. While it offers additional features, support, and a more user-friendly interface, it might not be affordable for all organizations.

NumPy videos

+ Add

Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Nagios videos

+ Add

Stop using Nagios - Andy Sykes

More videos:

  • Review - Bernd Erk - Why favour Icinga over Nagios
  • Review - How Nagios XI Works

Category Popularity

0-100% (relative to NumPy and Nagios)

NumPy

Nagios

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Monitoring Tools
0 0%
Monitoring Tools
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Log Management
0 0%
Log Management
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 NumPy and Nagios

NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
Source: www.analyticsvidhya.com
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Nagios Reviews

11 Best Nagios Alternatives (Free & Open Source) in 2024
Nagios is an open source network monitoring solution. It helps organizations to identify and resolve IT infrastructure issues. However, Nagios could be difficult integrate into automatic provisioning processes. There are few other issues with Nagios as well. Here, is a curated list of top tools that can replace Nagios. This list consists of paid as well as open-source...
Source: www.guru99.com
The Best Nagios Alternatives for Server, Application and Network Monitoring
Nagios is a very strong system monitoring package but its ability to compete in both the free and paid system monitoring market is frequently challenged. The free tool is very comprehensive. However, the Nagios team has taken away the traffic analysis functions from this, moving them off into a separate paid tool, which puts Nagios Core at a disadvantage when compared to...
Source: www.websentra.com
The 10 Best Nagios Alternatives in 2024 (Paid and Open-source)
It’s also important to note that Nagios is completely open-source, which means that it’s free to use. However, “free to use” doesn’t mean that it won’t cost you anything. Often, the reason users look for alternatives to tools like Nagios is because of their open-source nature. Self-hosting a tool of this magnitude can be even more expensive than purchasing a SaaS subscription.
Source: betterstack.com
The Best Cacti Monitoring Alternatives
Nagios is free for small environments with seven or fewer nodes and hosts. Its paid version starts at $1995 for the license and is priced per user. There is also a variety of free training options for Nagios available online. Both of Nagios’ paid versions include a free trial.
Source: www.webservertalk.com
10 Best Linux Monitoring Tools and Software to Improve Server Performance [2022 Comparison]
Nagios Core is an open-source Linux/Unix systems monitoring and alerting tool that can be extended through custom plugins, providing flexible Linux server monitoring. It remotely executes different plugins (executables or scripts) on your Linux server using the NRPE (Nagios Remote Plugin Executor) add-on, which gives you comprehensive monitoring data, including OS metrics,...
Source: sematext.com

Social recommendations and mentions

Based on our record, NumPy seems to be more popular. It has been mentiond 119 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.

NumPy mentions (119)

  • Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
    The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 3 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 7 months ago
  • Intro to Ray on GKE
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 8 months ago
  • Streamlit 101: The fundamentals of a Python data app
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 9 months ago
  • A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
    The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 9 months ago
View more

Nagios mentions (0)

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

What are some alternatives?

When comparing NumPy and Nagios, you can also consider the following products

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

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

OpenCV - OpenCV is the world's biggest computer vision library

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.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

NewRelic - New Relic is a Software Analytics company that makes sense of billions of metrics across millions of apps. We help the people who build modern software understand the stories their data is trying to tell them.

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