Software Alternatives, Accelerators & Startups

Ahrefs VS TensorFlow

Compare Ahrefs VS TensorFlow and see what are their differences

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.

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!

TensorFlow logo TensorFlow

TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
  • 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.

  • TensorFlow Landing page
    Landing page //
    2023-06-19

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.

TensorFlow features and specs

  • Comprehensive Ecosystem
    TensorFlow offers a complete ecosystem for end-to-end machine learning, covering everything from data preprocessing, model building, training, and deployment to production.
  • Community and Support
    TensorFlow boasts a large and active community, as well as extensive documentation and tutorials, making it easier for beginners to learn and experts to get help.
  • Flexibility
    TensorFlow supports a wide range of platforms such as CPUs, GPUs, TPUs, mobile devices, and embedded systems, providing flexibility depending on the user's needs.
  • Integrations
    TensorFlow integrates well with other Google products and services, including Google Cloud, facilitating seamless deployment and scaling.
  • Versatility
    TensorFlow can be used for a wide range of applications from simple neural networks to more complex projects, including deep learning and artificial intelligence research.

Possible disadvantages of TensorFlow

  • Complexity
    TensorFlow can be challenging to learn due to its complexity and the steep learning curve, particularly for beginners.
  • Performance Overhead
    Although TensorFlow is powerful, it can sometimes exhibit performance overhead compared to other, lighter frameworks, leading to longer training times.
  • Verbose Syntax
    The code in TensorFlow tends to be more verbose and less intuitive, which can make writing and debugging code more cumbersome relative to other frameworks like PyTorch.
  • Compatibility Issues
    Frequent updates and changes can lead to compatibility issues, requiring significant effort to keep libraries and dependencies up to date.
  • Mobile Deployment
    While TensorFlow supports mobile deployment, it is less optimized for mobile platforms compared to some other specialized frameworks, leading to potential performance drawbacks.

Ahrefs videos

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]

TensorFlow videos

What is Tensorflow? - Learn Tensorflow for Machine Learning and Neural Networks

More videos:

  • Tutorial - TensorFlow In 10 Minutes | TensorFlow Tutorial For Beginners | Deep Learning & TensorFlow | Edureka
  • Review - TensorFlow in 5 Minutes (tutorial)

Category Popularity

0-100% (relative to Ahrefs and TensorFlow)
SEO Tools
100 100%
0% 0
Data Science And Machine Learning
SEO
100 100%
0% 0
AI
59 59%
41% 41

User comments

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Reviews

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

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.
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.
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.
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.

TensorFlow Reviews

7 Best Computer Vision Development Libraries in 2024
From the widespread adoption of OpenCV with its extensive algorithmic support to TensorFlow's role in machine learning-driven applications, these libraries play a vital role in real-world applications such as object detection, facial recognition, and image segmentation.
10 Python Libraries for Computer Vision
TensorFlow and Keras are widely used libraries for machine learning, but they also offer excellent support for computer vision tasks. TensorFlow provides pre-trained models like Inception and ResNet for image classification, while Keras simplifies the process of building, training, and evaluating deep learning models.
Source: clouddevs.com
25 Python Frameworks to Master
Keras is a high-level deep-learning framework capable of running on top of TensorFlow, Theano, and CNTK. It was developed by François Chollet in 2015 and is designed to provide a simple and user-friendly interface for building and training deep learning models.
Source: kinsta.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
TensorFlow is an open-source software library for dataflow and differentiable programming across a range of tasks such as machine learning, computer vision, and natural language processing. It provides excellent support for deep learning models and is widely used in several industries. TensorFlow offers several pre-trained models for image classification, object detection,...
Source: www.uubyte.com
PyTorch vs TensorFlow in 2022
There are a couple of notable exceptions to this rule, the most notable being that those in Reinforcement Learning should consider using TensorFlow. TensorFlow has a native Agents library for Reinforcement Learning, and Deepmind’s Acme framework is implemented in TensorFlow. OpenAI’s Baselines model repository is also implemented in TensorFlow, although OpenAI’s Gym can be...

Social recommendations and mentions

Based on our record, Ahrefs seems to be a lot more popular than TensorFlow. While we know about 118 links to Ahrefs, we've tracked only 7 mentions of TensorFlow. 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.

Ahrefs mentions (118)

  • 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 / 4 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 / 29 days 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
  • How to scrape Crunchbase using Python in 2024 (Easy Guide)
    Sitemap is a standard way of site navigation used by crawlers like Google, Ahrefs, and other search engines. All crawlers must follow the rules described in robots.txt. - Source: dev.to / 5 months ago
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TensorFlow mentions (7)

  • Creating Image Frames from Videos for Deep Learning Models
    Converting the images to a tensor: Deep learning models work with tensors, so the images should be converted to tensors. This can be done using the to_tensor function from the PyTorch library or convert_to_tensor from the Tensorflow library. - Source: dev.to / over 2 years ago
  • Need help with a Tensorflow function
    So I went to tensorflow.org to find some function that can generate a CSR representation of a matrix, and I found this function https://www.tensorflow.org/api_docs/python/tf/raw_ops/DenseToCSRSparseMatrix. Source: almost 3 years ago
  • Help: Slow performance with windows 10 compared to Ubuntu 20.04 with TF2.7
    Can anyone offer up an explanation for why there is a performance difference, and if possible, what could be done to fix it. I'm using the installation guidelines found on tensorflow.org and installing tf2.7 through pip using an anaconda3 env. Source: about 3 years ago
  • [Question] What are the best tutorials and resources for implementing NLP techniques on TensorFlow?
    I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org. Source: about 3 years ago
  • [Question] What are the best tutorials and resources for implementing NLP techniques on TensorFlow?
    I have looked at this TensorFlow website and TensorFlow.org and some of the examples are written by others, and it seems that I am stuck in RNNs. What is the best way to install TensorFlow, to follow the documentation and learn the methods in RNNs in Python? Is there a good tutorial/resource? Source: about 3 years ago
View more

What are some alternatives?

When comparing Ahrefs and TensorFlow, you can also consider the following products

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

PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...

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

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

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.

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