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n8n.io VS TensorFlow

Compare n8n.io VS TensorFlow and see what are their differences

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n8n.io logo n8n.io

Free and open fair-code licensed node based Workflow Automation Tool. Easily automate tasks across different services.

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.
  • n8n.io Landing page
    Landing page //
    2024-06-26
  • TensorFlow Landing page
    Landing page //
    2023-06-19

n8n.io

Website
n8n.io
$ Details
freemium $20.0 / Monthly
Platforms
Browser TypeScript JavaScript Web Linux Docker Windows Mac OSX
Release Date
2019 January
Startup details
Country
Germany
State
Berlin
City
Berlin
Employees
10 - 19
Edit details

TensorFlow

Website
tensorflow.org
$ Details
Platforms
-
Release Date
-
Edit details

n8n.io features and specs

  • Open Source
    n8n.io is open-source, allowing users to modify and extend the platform as needed. This ensures transparency and community-driven improvements.
  • Flexibility
    The platform provides a high degree of flexibility, supporting a wide range of automation scenarios and custom workflow configurations.
  • Extensive Integrations
    n8n.io supports many third-party integrations, making it easy to connect various applications and services in workflows.
  • Self-hosting Option
    Users can choose to self-host n8n.io, which provides greater control over data security and privacy.
  • Visual Interface
    The visual workflow builder makes it easy for users to design and manage workflows without needing extensive coding knowledge.

Possible disadvantages of n8n.io

  • Learning Curve
    Due to its flexibility and range of features, n8n.io can have a steeper learning curve for beginners compared to more straightforward automation tools.
  • Performance
    Performance can be an issue for complex workflows or high-volume operations, especially when self-hosted on basic infrastructure.
  • Documentation
    While improving, documentation can sometimes be lacking or not comprehensive, making it challenging for new users to find necessary information.
  • Limited Support
    As an open-source project, professional support may be limited compared to commercial automation platforms, which might offer more robust support options.
  • Cost for Cloud Hosting
    n8n.io offers a cloud-hosted version with a subscription fee, which could be a downside for users looking for a completely free solution.

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.

n8n.io videos

+ Add

n8n.io - Typeform to Google Sheet and Slack or Email

More videos:

  • Review - n8n.cloud | Powerful workflow automation tool
  • Review - Get started with n8n.cloud (Part 1)
  • Review - n8n.io - Slack Notification on Github Star

TensorFlow videos

+ Add

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 n8n.io and TensorFlow)

n8n.io

TensorFlow

Automation
100 100%
Automation
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Web Service Automation
100 100%
Web Service Automation
0% 0
AI
0 0%
AI
100% 100

User comments

Share your experience with using n8n.io and TensorFlow. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare n8n.io and TensorFlow

n8n.io Reviews

The Best n8n.io Alternatives for Workflow Automation in 2025
} } AlternativesRadzivon AlkhovikLow-code automation enthusiastSeptember 17, 2024A low-code platform blending no-code simplicity with full-code power 🚀Get started freeHome/Blog/The Best n8n.io Alternatives for Workflow Automation in 2025 .ellipsis { max-width: 100%; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; } September 17, 2024•10min readThe Best n8n.io...
Source: latenode.com
The 6 Best n8n.io Alternatives for 2024
When you're trying to automate your repetitive tasks, it often feels like you're spinning a bunch of plates in the air and making zero progress, doesn't it? You're far from alone. If you use n8n.io for your workflow automation and are left needing more, then you should take a look at the best n8n.io alternatives.
Source: www.getmagical.com
N8n.io Alternatives
As businesses increasingly seek efficient workflow automation tools, N8n.io has emerged as a popular choice. However, it's not the only option available. This article explores some of the best N8n.io alternatives, considering factors like ease of use, integration capabilities, and pricing. Whether you're a startup or an established enterprise, finding the right tool can...
Source: apix-drive.com
13 data integration tools: a comparative analysis of the top solutions
A standout feature of n8n is the self-hosted mode (even on a free tier!), which allows data ownership and control. For those who value data ownership and want to avoid high-cost operations, n8n is certainly a worthy consideration.
Source: blog.n8n.io
10 n8n.io Alternatives
n8n.io is a sleek and simple workflow automation platform that never indulges you in unnecessary things and boosts your productivity while letting you focus only on productive things. Some of its super reliable functions are free and open-source, fair code license, easily extendable, and extreme data safety and security. Get on n8n.io – Automate without Limits Tool to know...
Source: www.justalternativeto.com

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.
Source: www.labellerr.com
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...
Source: www.assemblyai.com

Social recommendations and mentions

Based on our record, n8n.io seems to be a lot more popular than TensorFlow. While we know about 182 links to n8n.io, 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.

n8n.io mentions (182)

  • 🤖 Automating WhatsApp with AI Agents: A Developer's Guide to Scalable Customer Support
    To set up such a system, developers can take advantage of tools like n8n – a modular tool to automate workflows, combined with the newest AI tools like GPT-4. Here’s a more detailed explanation. - Source: dev.to / 2 days ago
  • I made my AI think harder by making it argue with itself. It works stupidly well
    The app is actually called n8n - https://n8n.io/. - Source: Hacker News / 3 days ago
  • Integrating AI Agents with n8n: Enhance Your Workflow Automation
    For those interested in elevating their automation capabilities, n8n offers an array of integrations worth exploring. Visit n8n.io if you're intrigued. - Source: dev.to / 22 days ago
  • Harnessing AI Automation with n8n for Seamless Blog Writing
    If you're thinking of exploring similar automation paths, I highly recommend n8n. It's an excellent platform that offers great flexibility to build your AI workflows. Check it out at n8n.io and see how it might simplify your processes as it has mine. 🚀. - Source: dev.to / 25 days ago
  • Self-hosting n8n on Ubuntu Server
    Want to automate tasks using n8n but prefer to fully control your infrastructure? By self-hosting n8n on a Linux Ubuntu server, you can cut down costs and manage your data yourself! - Source: dev.to / 30 days ago
View more

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 / about 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: almost 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 n8n.io and TensorFlow, you can also consider the following products

Zapier - Connect the apps you use everyday to automate your work and be more productive. 1000+ apps and easy integrations - get started in minutes.

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

Make.com - Tool for workflow automation (Former Integromat)

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

ifttt - IFTTT puts the internet to work for you. Create simple connections between the products you use every day.

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

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