Software Alternatives, Accelerators & Startups
Register | Login

Airtable VS PyTorch

Compare Airtable VS PyTorch and see what are their differences

monday.com
The most intuitive platform to manage projects and teamwork 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

Airtable logo Airtable

Airtable works like a spreadsheet but gives you the power of a database to organize anything. Sign up for free.

PyTorch logo PyTorch

Open source deep learning platform that provides a seamless path from research prototyping to...
  • Airtable Landing page
    Landing page //
    2023-10-19
  • PyTorch Landing page
    Landing page //
    2023-07-15

Airtable

Website
airtable.com
Pricing URL
Official Airtable Pricing
$ Details
-
Release Date
2013 January
Startup details
Country
United States
State
California
City
San Francisco
Founder(s)
Andrew Ofstad
Employees
250 - 499
Edit details

PyTorch

Website
pytorch.org
Pricing URL
-
$ Details
Release Date
-
Edit details

Airtable features and specs

  • User-Friendly Interface
    Airtable provides an intuitive, visually appealing interface that makes it easy for users to create, manage, and navigate complex data sets without extensive technical knowledge.
  • Customizability
    Airtable offers robust customization options, allowing users to tailor databases and views to their specific needs, including various field types, multiple views, and linked records.
  • Collaboration Features
    Airtable supports real-time collaboration, enabling multiple users to work on the same database simultaneously while tracking changes and maintaining version history.
  • Integrations
    Airtable integrates with various third-party applications and services such as Slack, Google Drive, and Zapier, allowing for seamless workflow automation and enhanced productivity.
  • Templates
    Airtable offers a wide range of pre-built templates for different use cases, which helps users get started quickly without having to build everything from scratch.
  • Mobile App
    Airtable's mobile application allows users to access and manage their databases on the go, ensuring flexibility and continuous productivity.

Possible disadvantages of Airtable

  • Cost
    While Airtable offers a free tier, many of the more advanced features and higher usage limits are locked behind a subscription model, which can become costly for larger teams or extensive use.
  • Performance Issues
    Some users have reported performance issues with Airtable when working with very large databases, including slow load times and laggy interface responsiveness.
  • Limited Offline Access
    Airtable relies heavily on an internet connection, and its offline capabilities are limited, which may be a drawback for users who need consistent access without reliable internet.
  • Data Export Options
    Data export options are somewhat limited compared to other database management tools, making it more difficult to extract data in certain formats for use outside of Airtable.
  • Learning Curve
    Despite its user-friendly interface, the extensive features and customizability of Airtable can present a learning curve for new users, requiring time to explore and understand its full capabilities.
  • Lack of Advanced Features
    Airtable may lack some advanced features found in more specialized or traditional database management systems, making it less suitable for particularly complex or highly specific data management needs.

PyTorch features and specs

  • Dynamic Computation Graph
    PyTorch uses a dynamic computation graph, which allows for interactive and flexible model building. This is particularly beneficial for researchers who need to modify the network architecture on-the-fly.
  • Pythonic Nature
    PyTorch is designed to be deeply integrated with Python, making it very intuitive for Python developers. The framework feels more 'native' to Python, which improves the ease of learning and use.
  • Strong Community Support
    PyTorch has a large, active, and growing community. This means abundant resources such as tutorials, forums, and third-party tools are available to help developers solve problems and share solutions.
  • Flexibility and Control
    PyTorch offers granular control over computations and provides extensive debugging capabilities. This level of control is beneficial for tasks that require precise tuning and custom implementations.
  • Support for GPU Acceleration
    PyTorch offers seamless integration with GPU hardware, which significantly accelerates the computation process. This makes it highly efficient for deep learning tasks.
  • Rich Ecosystem
    PyTorch has a rich ecosystem including libraries like torchvision, torchaudio, and torchtext, which are specialized for different data types and can significantly shorten development times.

Possible disadvantages of PyTorch

  • Limited Production Deployment Tools
    PyTorch is primarily designed for research rather than production. While deployment tools like TorchServe exist, they are not as mature or integrated as solutions offered by other frameworks like TensorFlow.
  • Lesser Adoption in Industry
    While PyTorch is popular among researchers, it has historically seen less adoption in industry compared to TensorFlow, which means there might be fewer resources for large-scale production deployments.
  • Inconsistent API Changes
    As PyTorch continues to evolve rapidly, occasionally there are breaking changes or inconsistent API updates. This can create maintenance challenges for existing codebases.
  • Steeper Learning Curve for Beginners
    Despite its Pythonic design, PyTorch's focus on flexibility and control can make it slightly harder for beginners to get started compared to some other high-level libraries and frameworks.
  • Less Mature Documentation
    Although the documentation is improving, it has been historically less comprehensive and mature compared to other frameworks like TensorFlow, which can make it difficult to find detailed, clear information.

Airtable videos

+ Add

Airtable Review | Features, Pricing & Team Use

More videos:

  • Tutorial - Airtable API Tutorial With cURL and JavaScript
  • Review - Airtable Blocks for Project Management
  • Review - Airtable vs. Google Sheets
  • Review - airtable review

PyTorch videos

+ Add

PyTorch in 5 Minutes

More videos:

  • Review - Jeremy Howard: Deep Learning Frameworks - TensorFlow, PyTorch, fast.ai | AI Podcast Clips
  • Review - PyTorch at Tesla - Andrej Karpathy, Tesla

Category Popularity

0-100% (relative to Airtable and PyTorch)

Airtable

PyTorch

Project Management
100 100%
Project Management
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
No Code
100 100%
No Code
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using Airtable and PyTorch. 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 Airtable and PyTorch

Airtable Reviews

  1. Sanjana Shah
    · Data Scientist at Boston Institute of Analytics ·
    Airtable: Spreadsheets + Databases = Efficiency

    Airtable is a powerful cloud-based software that combines spreadsheets and databases, offering real-time collaboration and customizable features for efficient task management1.

    🏁 Competitors: monday.com, ClickUp, Smartsheet
    👍 Pros:    Free forever plan and affordable paid options starting at $10 per month.|Visually appealing and user-friendly interface.|Pre-made templates for easy setup and use.|Real-time collaboration and communication.|Customizable features for task management.
    👎 Cons:    Limited project customization without a paid plan.|Top-tier accounts required for gantt tools.|May take time to learn and grasp advanced features.
The Top 7 ClickUp Alternatives You Need to Know in 2025
Benefits:Airtable's ability to integrate various data sources into one platform allows teams to maintain a centralized source of truth while leveraging powerful visualization tools6.
Source: www.ledgerteams.com
Top 10 Notion Alternatives for 2025 and Why Teams Are Choosing Ledger
Airtable blends spreadsheets with database features, offering teams a powerful way to organize structured information. While its flexibility is impressive, it's not purpose-built for communication or team collaboration at scale.
Source: www.ledgerteams.com
25 Best Asana Alternatives & Competitors for Project Management in 2024
Airtable is one of the most popular Asana alternatives. It’s project management tool that helps teams create detailed databases for their work. Users can group and sort data in custom fields with views like Grid to include only the relevant project information.
Source: clickup.com
Top 10 Microsoft Power Apps Alternatives and Competitors 2024
Airtable Pricing: Airtable offers a freemium plan with limited features for individual users. Paid plans start at $10 per user per month for additional features and functionalities. Enterprise plans with custom pricing cater to large-scale deployments.
Source: medium.com
The 10 best Asana alternatives in 2024
If you're looking for a project management app that leans more toward data management, try Airtable. Out of the box, Airtable's default view looks like a spreadsheet. It offers a few project templates based on your team type (such as marketing or sales), or you can build a "base" from scratch. From there, you can add highly customizable fields (or columns) to each row, so...
Source: zapier.com

PyTorch Reviews

10 Python Libraries for Computer Vision
Similar to TensorFlow and Keras, PyTorch and torchvision offer powerful tools for computer vision tasks. PyTorch’s dynamic computation graph and torchvision’s datasets and pre-trained models make it easy to implement tasks such as image classification, object detection, and style transfer.
Source: clouddevs.com
25 Python Frameworks to Master
Along with TensorFlow, PyTorch (developed by Facebook’s AI research group) is one of the most used tools for building deep learning models. It can be used for a variety of tasks such as computer vision, natural language processing, and generative models.
Source: kinsta.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
PyTorch is another open-source machine learning framework that is widely used in academia and industry. PyTorch provides excellent support for building deep learning models, and it has several pre-trained models for computer vision tasks, making it the ideal tool for several computer vision applications. PyTorch offers a user-friendly interface that makes it easier for...
Source: www.uubyte.com
PyTorch vs TensorFlow in 2022
When we compare HuggingFace model availability for PyTorch vs TensorFlow, the results are staggering. Below we see a chart of the total number of models available on HuggingFace that are either PyTorch or TensorFlow exclusive, or available for both frameworks. As we can see, the number of models available for use exclusively in PyTorch absolutely blows the competition out of...
Source: www.assemblyai.com
15 data science tools to consider using in 2021
First released publicly in 2017, PyTorch uses arraylike tensors to encode model inputs, outputs and parameters. Its tensors are similar to the multidimensional arrays supported by NumPy, another Python library for scientific computing, but PyTorch adds built-in support for running models on GPUs. NumPy arrays can be converted into tensors for processing in PyTorch, and vice...
Source: searchbusinessanalytics.techtarget.com

Social recommendations and mentions

PyTorch might be a bit more popular than Airtable. We know about 132 links to it since March 2021 and only 130 links to Airtable. 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.

Airtable mentions (130)

  • How to Build Internal Tools 100x Faster
    It is possible to speed up the development and delivery process for many internal applications by using no-code or low code tools. These vary in offerings from open source to SaaS, including popular ones like AirTable, BudiBase, Retool, NocoDB and others. These can all greatly help speed up delivery times. - Source: dev.to / 5 months ago
  • Growing a side-project to 100k Unique Visitors in one week
    For the backend, I opted for Airtable as a database. It's a simple, no-code solution that I've used before. It's not the most powerful database, but it's perfect for a project like this. I could easily add, edit, and delete records, and it has an embeddable form functionality that I used for user submissions. - Source: dev.to / about 1 year ago
  • A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
    Airtable.com — Looks like a spreadsheet, but it's a relational database unlimited bases, 1,200 rows/base, and 1,000 API requests/month. - Source: dev.to / over 1 year ago
  • How to generate links to a record to view it in an Interface?
    The ?XXXXX part of the URL identifies the type of interface page it is. Just copy that and then your formula is just "https://airtable.com.../...?XXXXXX=" & RECORD_ID() I'm not sure it works in every type of interface page (where you've started from a blank page for example). There has to be something to identify the record viewed from the page, if you see what I mean. Source: over 1 year ago
  • Working on a personal app for data tracking. looking for suggestions
    So I started building something on airtable.com that would allow me to easily track updates for each batch. What in your experience would make sense to track that I may be missing? Source: over 1 year ago
View more

PyTorch mentions (132)

  • Top Programming Languages for AI Development in 2025
    With the quick emergence of new frameworks, libraries, and tools, the area of artificial intelligence is always changing. Programming language selection. We're not only discussing current trends; we're also anticipating what AI will require in 2025 and beyond. - Source: dev.to / 10 days ago
  • Fine-tuning LLMs locally: A step-by-step guide
    Next, we define a training loop that uses our prepared data and optimizes the weights of the model. Here's an example using PyTorch:. - Source: dev.to / about 1 month ago
  • 10 Must-Have AI Tools to Supercharge Your Software Development
    8. TensorFlow and PyTorch: These frameworks support AI and machine learning integrations, allowing developers to build and deploy intelligent models and workflows. TensorFlow is widely used for deep learning applications, offering pre-trained models and extensive documentation. PyTorch provides flexibility and ease of use, making it ideal for research and experimentation. Both frameworks support neural network... - Source: dev.to / 3 months ago
  • Automating Enhanced Due Diligence in Regulated Applications
    Frameworks like TensorFlow and PyTorch can help you build and train models for various tasks, such as risk scoring, anomaly detection, and pattern recognition. - Source: dev.to / 3 months ago
  • Must-Know 2025 Developer’s Roadmap and Key Programming Trends
    Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 3 months ago
View more

What are some alternatives?

When comparing Airtable and PyTorch, you can also consider the following products

Asana - Asana project management is an effort to re-imagine how we work together, through modern productivity software. Fast and versatile, Asana helps individuals and groups get more done.

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.

Trello - Infinitely flexible. Incredibly easy to use. Great mobile apps. It's free. Trello keeps track of everything, from the big picture to the minute details.

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

Basecamp - A simple and elegant project management system.

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

Loading...