Software Alternatives, Accelerators & Startups
Register | Login

NumPy VS Ahrefs

Compare NumPy VS Ahrefs and see what are their differences

happySEO
Create ai humanized SEO content tailored for ecommerce and small businesses with HappySEO tools. From ai writer to keyword research and analyze tools. featured
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.
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Ahrefs logo Ahrefs

Ahrefs is a toolset for SEO and marketing. We have tools for backlink research, organic traffic research, keyword research, content marketing & more. Give Ahrefs a try!
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Ahrefs Landing page
    Landing page //
    2023-10-11

Ahrefs is trusted by SEOs and marketing professionals worldwide as the ultimate toolset for SEO, powered by industry-leading data. Ahrefs crawls the web, stores tons of data and makes it easily accessible via a simple user interface. The data can be used to aid keyword research, link building, content marketing and SEO strategies. Ultimately, the tool helps to accelerate the growth of organic search traffic to a website.

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.

Ahrefs features and specs

  • Comprehensive Data
    Ahrefs offers extensive data on backlinks, keywords, and site audits, allowing users to make well-informed decisions on their SEO strategies.
  • User-Friendly Interface
    The platform has an intuitive and easy-to-navigate interface, making it accessible for both beginners and experienced SEO professionals.
  • Accurate Backlink Analysis
    Ahrefs is known for its accurate and up-to-date backlink data, which is crucial for comprehensive SEO analysis and strategy development.
  • Robust Keyword Research
    The keyword research tools in Ahrefs provide detailed information and insights, helping users to identify valuable keywords for their content.
  • Site Audit Capabilities
    Ahrefs' site audit feature helps identify and fix on-site SEO issues, improving overall website health and performance.
  • Continuous Updates
    Ahrefs frequently updates its database and introduces new features, ensuring users have access to the latest SEO tools and data.
  • Competitive Analysis
    The platform allows users to analyze competitor websites in-depth, giving insights into their strategies and helping to identify opportunities.

Possible disadvantages of Ahrefs

  • High Cost
    Ahrefs is relatively expensive compared to other SEO tools, which may be a barrier for small businesses or individual users with limited budgets.
  • Learning Curve
    Despite its user-friendly interface, the vast array of features and data can initially be overwhelming for new users, requiring time to master.
  • Limited Access in Basic Plan
    The lower-tier plans limit access to certain data and features, potentially necessitating an upgrade to higher-cost plans for full functionality.
  • No Free Trial
    Ahrefs does not offer a free trial, which can make it challenging for potential users to fully assess its value before committing to a subscription.
  • API Limitations
    Access to the API is restricted and may not be comprehensive enough for advanced users requiring extensive data integration capabilities.
  • Occasional Data Gaps
    Despite frequent updates, there may occasionally be gaps or delays in data, particularly for niche or emerging markets.
  • Limited Customer Support Options
    Customer support is mainly provided via email, which might not be sufficient for urgent issues or users preferring instant support options like live chat.

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.

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

Ahrefs videos

+ Add

Ahrefs Review and Tutorial: Is This The Only SEO Tool You Need?

More videos:

  • Review - Ahrefs Review | FatRank Ahref Testimonial
  • Tutorial - How to Use Ahrefs Tool - Best Premium SEO Tools [2019]

Category Popularity

0-100% (relative to NumPy and Ahrefs)

NumPy

Ahrefs

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
SEO Tools
0 0%
SEO Tools
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
SEO
0 0%
SEO
100% 100

User comments

Share your experience with using NumPy and Ahrefs. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare NumPy and Ahrefs

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

Ahrefs Reviews

  1. Cyra Brown
    · Owner at Beginu ·
    Excellent for discovering low competition keywords

    I've enjoyed using Ahrefs to inform content creation due to their keyword explorer being so useful for finding low difficulty keywords. I do prefer the legacy version of their site explorer in comparison to the new format so I hope that they do not retire certain elements of the platform.

    🏁 Competitors: SEMRush
The 16 Best Moz Alternatives for Every Budget 
Unlike competitors, Ahrefs doesn’t offer a free trial. To start using Ahrefs, you must purchase the Lite plan for $129.
Source: trafficthinktank.com
10 SE Ranking Alternatives in 2025 [Free and Paid]
Users appreciate Moz Pro for its user-friendly design and accurate rank tracking, making it accessible to both beginners and experienced marketers. However, some users feel it lacks the depth in backlink analysis offered by tools like Ahrefs, which may limit its appeal for those focusing on link-building.
Source: www.madx.digital
10 Moz Pro Alternatives in 2025 [Free and Paid]
Starting at $129/month, Ahrefs is slightly more expensive than Moz Pro but offers advanced features that justify the investment. For users who require detailed backlink data and in-depth SEO analysis, Ahrefs is a top choice.
Source: www.madx.digital
The best alternatives to SE Ranking in 2024
But all this comes at a price. Ahrefs is quite expensive, especially considering that even with a subscription, its use is not unlimited. At the beginning of each month, you are allocated a number of credits, which varies depending on the plan, and these credits are depleted as you use many of its features. And believe me, the credits run out faster than you realize.
Source: dinorank.com
Top 6 Moz Competitors In 2024: A Detailed Review
Furthermore, Ahrefs excels in providing users with in-depth backlink data. It helps to uncover new link-building opportunities and analyze competitors’ backlink strategies. Its user-friendly interface and accurate data make it a favorite among SEO professionals.
Source: www.flyingvgroup.com

Social recommendations and mentions

Ahrefs might be a bit more popular than NumPy. We know about 119 links to it since March 2021 and only 119 links to NumPy. 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 / 5 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 / 9 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 / 9 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 / 10 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 / 10 months ago
View more

Ahrefs mentions (119)

  • Generating Content with ChatGPT
    I’ve been using the most excellent ARefs site to get information about how good the on-page SEO is for many of my sites. Every couple of weeks, ARefs crawls the site and will give me a list of suggestions of things I can improve. And for a long time, I had been putting off dealing with one of the biggest issues – because it seemed so difficult. - Source: dev.to / 7 days ago
  • How We Marketed a Niche SaaS Product with Zero Budget: 9 Strategies That Actually Worked
    Pro tip: Use Ahrefs or Ubersuggest to find long-tail gold. - Source: dev.to / 13 days ago
  • Ask HN: How to Get Good at SEO?
    I recently "launched" my product by mentioning it across Twitter and Discord which led some traffic to it. However, that is not a long-term strategy. I have heard about Ahrefs: https://ahrefs.com/, but I don't want to spend $129 right now since I'm not sure whether the ROI on it would be worth it. Are there any strategies or tips you might be able to share? - Source: Hacker News / about 1 month ago
  • Open source Google Analytics replacement
    Posthog is pretty good but very pushy towards using their SaaS (understandably). Self hosting is not really advertised on their main site however is buried in their gh repo as a footnote [1] with indications of vague issues past 100K events/month. Haven’t delved into how to scale it past that though and they do provide some docs that I have yet to review. Also the primary repo is not FOSS, and that "100% FOSS"... - Source: Hacker News / about 1 month ago
  • What We Did to Gain 3,000 GitHub Stars for the Liam Repository
    Used Ahrefs to check backlinks of competitors and similar products, adding sites that featured those products to our list of candidates. - Source: dev.to / about 2 months ago
View more

What are some alternatives?

When comparing NumPy and Ahrefs, 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.

SEMRush - All-in-one Marketing Toolkit for digital marketing professionals.

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

Moz - Backed by industry-leading data and the largest community of SEOs on the planet, Moz builds tools that make inbound marketing easy.

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

Serpstat - Serpstat is the Swiss army knife for automating SEO processes. With a suite of powerful modules, you can track your performance, analyze your competitors, research keywords and backlinks, audit your website, and so much more.

Loading...