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phpIPAM VS NumPy

Compare phpIPAM VS NumPy and see what are their differences

phpIPAM

phpipam is an open-source web IP address management application (IPAM).

Rating
0 reviews
Pricing
Open source
Alternatives Is it good?
NumPy

NumPy is the fundamental package for scientific computing with Python

Rating
0 reviews
Pricing
Open source
Alternatives Is it good?
Bluebox.ai
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Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Which is more popular?

Based on our record, NumPy should be more popular than phpIPAM. It has been mentioned 122 times since March 2021.

social mentions
19 vs 122
Monitoring Tools popularity
100% vs 0%
alternatives listed
66 vs 189

Base details

Website, pricing, platforms and company facts side by side.

phpIPAM
NumPy
Website phpipam.net numpy.org
Pricing
Open source
Open source
Listed in
Monitoring Tools Log Management Network & Admin DNS Tools +1
Data Science And Machine Learning Data Science Tools Python Tools Software Libraries +1

Features and specs

What each product offers, as listed by its team.

phpIPAM 6 features
NumPy 5 features
  • Open Source
    phpIPAM is an open source IP address management (IPAM) software, which means that it's freely available and can be modified to suit specific needs without any licensing fees.
  • Web-Based Interface
    The tool provides a user-friendly, web-based interface that enables easy access and management of IP addresses from anywhere with an internet connection.
  • Feature-Rich
    phpIPAM comes with a comprehensive set of features, including VLAN management, subnet management, and device tracking, which are essential for effective network management.
  • Integrations
    phpIPAM supports various integrations with other systems, such as DNS servers and DHCP servers, to provide a more cohesive and automated network management experience.
  • Active Community Support
    There is an active community around phpIPAM that contributes to its development and provides support, making it easier to find solutions to common problems.
  • Scalability
    The software is designed to scale well, making it suitable for both small and large networks without significant performance degradation.

Possible disadvantages

  • Complex Installation
    Setting up phpIPAM may require some technical know-how, particularly in configuring web servers, databases, and ensuring all dependencies are met.
  • Limited Vendor Support
    As an open source project, phpIPAM might not offer the same level of professional support and documentation as some commercial IPAM solutions.
  • User Interface
    While functional, the user interface of phpIPAM may not be as polished or intuitive as some other commercial alternatives, which can affect user experience.
  • Update Management
    Managing updates and ensuring compatibility with existing systems can require careful planning and can sometimes lead to disruptions.
  • Learning Curve
    New users, especially those without a background in network management, may find the learning curve steep, requiring time to fully grasp all the available features.
  • 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

  • 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.

Analysis

An editorial look at what each product does well and who it suits.

phpIPAM
NumPy

Overall verdict

  • phpIPAM is generally considered a good solution for IP address management, especially for organizations looking for an open-source and cost-effective tool. It effectively balances functionality, usability, and flexibility, making it suitable for a variety of network environments.

Why this product is good

  • Features
    It offers a comprehensive set of features such as IP address management, VLAN management, devices, racks, and circuit management, which are essential for network administrators.
  • Usability
    phpIPAM provides a user-friendly interface for managing and tracking IP addresses. Its web-based interface makes it accessible across different platforms.
  • Integration
    phpIPAM can integrate with other tools and services, such as DHCP servers, DNS servers, and cloud platforms, enhancing its functionality within a network environment.
  • Open source
    As an open-source project, phpIPAM allows for customization and extension by users, ensuring it can be tailored to specific organizational needs.

Recommended for

  • Network administrators in small to medium-sized enterprises
  • Organizations that need a cost-effective IP address management solution
  • IT professionals seeking an open-source tool with customization capabilities
  • Teams requiring a web-based IPAM solution that integrates with existing network infrastructure

Overall verdict

  • Yes, NumPy is considered good. It is a foundational library in the Python ecosystem for numerical computing and is used globally by researchers, engineers, and data scientists.

Why this product is good

  • NumPy is widely regarded as a good library because it offers fast, flexible, and efficient array handling that is integral to scientific computing in Python. It provides tools for integrating C/C++ and Fortran code, useful linear algebra, random number capabilities, and a vast collection of mathematical functions. Its array broadcasting capabilities and versatility make complex mathematical computations straightforward.

Recommended for

  • Scientists and researchers working with large-scale scientific computations.
  • Data scientists engaged in data analysis and manipulation.
  • Engineers and developers needing performance-optimized mathematical computations.
  • Educators and students in STEM fields.

Videos

Walkthroughs and reviews on video.

phpIPAM 3 videos + Add
NumPy 3 videos + Add

IPAM Server mit phpIPAM - IP adress management

More videos

  • - Foreman Integration with phpIPAM
  • - Apresentação PHPiPAM para provedores!

Learn NUMPY in 5 minutes - BEST Python Library!

More videos

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

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
phpIPAM
NumPy
100% 100%
Monitoring Tools
0% 0%
0% 0%
Data Science And Machine Learning
100% 100%
100% 100%
Log Management
0% 0%
0% 0%
Data Science Tools
100% 100%

User comments

Share your experience with using phpIPAM and NumPy. For example, how are they different and which one is better?

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Reviews and articles

External articles and on-site reviews we used to compare the two products.

phpIPAM no reviews yet
NumPy no reviews yet

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Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

phpIPAM 19 mentions
NumPy 122 mentions
  • Recommended free on-prem IPAM with integrated DNS solution?
    PHPIPAM does that, plus hardware inventory and racks (you assign the IP to a pice of hardware then put it on a rack and get rack diagram). It does also vLANs, VRF, circuits... Source: over 3 years ago
  • Looking for IPAM tools
    Given he info you provided, I would say phpipam. It is web base and very light on resources. I don't know if this counts in your portability requirement. https://phpipam.net/. Source: over 3 years ago
  • What is everyone using for IPAM (IP Management) for their home networks/labs ?
    Other than that, we use PHP IPAM at work. https://phpipam.net It’s fine. Source: over 3 years ago

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Alternatives to phpIPAM and NumPy

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

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