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Ping Identity VS NumPy

Compare Ping Identity VS NumPy and see what are their differences

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

Ping Identity logo Ping Identity

Ping Identity provides cloud-based, single sign-on and identity management solutions with their SAML SSO.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Ping Identity Landing page
    Landing page //
    2023-05-10
  • NumPy Landing page
    Landing page //
    2023-05-13

Ping Identity features and specs

  • Comprehensive Identity Management
    Ping Identity provides a wide range of identity management solutions, including single sign-on (SSO), multi-factor authentication (MFA), and API security, making it a complete package for enterprise identity management.
  • Scalability
    It is designed to scale efficiently with the growth of an organization, suitable for both small businesses and large enterprises.
  • Strong Security Features
    Ping Identity includes robust security features such as risk-based authentication, adaptive authentication, and threat detection capabilities.
  • User Experience
    The platform focuses on delivering seamless user experiences with features like password-less authentication and frictionless SSO across multiple applications.
  • Integration Capabilities
    It offers extensive integration capabilities with a wide range of applications, both on-premises and cloud-based, including popular SaaS providers.

Possible disadvantages of Ping Identity

  • Complexity
    Given the comprehensive nature of its features, Ping Identity can be complex to implement and may require specialized knowledge and expertise.
  • Cost
    The extensive range of features and scalability come at a cost, which might be prohibitive for smaller businesses with limited budgets.
  • Learning Curve
    Due to its sophisticated features, there is a steep learning curve for administrators and users who are new to the platform.
  • Customization
    While highly capable, customization for specific needs might require significant effort and sometimes additional support from Ping Identity.
  • Support Dependency
    Organizations may find themselves reliant on Ping Identity's support services for troubleshooting and maintenance, which could lead to higher ongoing costs.

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.

Analysis of Ping Identity

Overall verdict

  • Ping Identity is generally considered a good option for identity and access management solutions.

Why this product is good

  • Ping Identity is known for its robust security features, flexible deployment options, and comprehensive identity management capabilities. It offers a range of services including single sign-on, multi-factor authentication, and API security, which are appreciated by many enterprises. It also supports a wide variety of integrations and has a strong reputation for reliability and customer service.

Recommended for

    Ping Identity is well-suited for medium to large enterprises looking for scalable identity solutions, especially those wanting to enhance their security posture, achieve regulatory compliance, or improve the user experience with smoother access management.

Analysis of NumPy

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.

Ping Identity videos

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Okta vs. Ping Identity - Which Stock to Buy? Identity and Access Management (IAM) Cloud Stocks

More videos:

  • Review - Stocks Close Strong; Vertex, Ping Identity, ResMed Clear Buy Points

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

Category Popularity

0-100% (relative to Ping Identity and NumPy)

Ping Identity

NumPy

Identity And Access Management
100 100%
Identity And Access Management
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Identity Provider
100 100%
Identity Provider
0% 0
Data Science Tools
0 0%
Data Science Tools
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 Ping Identity and NumPy

Ping Identity Reviews

The Top 10 Single Sign-On Solutions For Business
Ping Identityโ€™s SSO solution is built to scale and enables staff to access all workspace applicationsโ€”whether mobile, cloud, enterprise, or SaaSโ€”using one set of credentials, via their centralized employee dock. This federated SSO is designed to work anywhere and from any device, and includes native support for identity standards such as SAML and OpenID Connect tokens, for...
Source: expertinsights.com
Top 10 Best SAML Identity Providers List for SSO (Pros and Cons)
Ping Identity features robust security, amazing end user experience, directory integration, and so much more. It is an intelligent identity platform that offers various cloud deployment offerings such as SSO solution, IDaaS (Identity as a service), containerized software, etc.
Source: cloudinfrastructureservices.co.uk
Top 11 Identity & Access Management Tools
Ping Identity is no slouch in other areas of IAM such as SSO, Data Access Governance, and User Directories. The product is not without complaints, mainly about its high price point and API communications. That said, it seems users are satisfied with the product and would recommend it even with those shortcomings.
Source: spectralops.io
Best identity access management software 2022
Ping Identity, founded in 2002 and one of the most well-established identity management companies in the business, was designed for hybrid IT environments. It works cleanly across public, private and hybrid clouds and with on-premises networks and applications.
Source: www.zdnet.com
The 6 Best Identity Access Management Tools
With Ping Identity we have another market leader in the IAM domain. Its solution is an ideal choice for organizations looking to enhance the security of their cloud-based assets without compromising on its customersโ€™ UI.
Source: www.comparitech.com

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

Social recommendations and mentions

Based on our record, NumPy seems to be more popular. It has been mentiond 122 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.

Ping Identity mentions (0)

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

NumPy mentions (122)

View more

What are some alternatives?

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

OneLogin - On-demand SSO, directory integration, user provisioning and more

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

Okta - Enterprise-grade identity management for all your apps, users & devices

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

Auth0 - Auth0 is a program for people to get authentication and authorization services for their own business use.

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

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