Software Alternatives, Accelerators & Startups

PyTorch VS AnyChart

Compare PyTorch VS AnyChart and see what are their differences

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PyTorch logo PyTorch

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

AnyChart logo AnyChart

Award-winning JavaScript charting library & Qlik Sense extensions from a global leader in data visualization! Loved by thousands of happy customers, including over 75% of Fortune 500 companies & over half of the top 1000 software vendors worldwide.
  • PyTorch Landing page
    Landing page //
    2023-07-15
  • AnyChart Home Page of AnyChart JS Charts
    Home Page of AnyChart JS Charts //
    2025-03-10

Founded in 2003, AnyChart is one of the global leaders in interactive data visualization, offering award-winning, flexible JavaScript (HTML5) charting libraries with numerous chart types and features, great API & documentation, and enterprise-grade support.

Cross-browser JS charts and graphs, maps, stock charts, and Gantt charts powered by AnyChart have helped thousands of companies including industry leaders โ€” from startups to corporate giants such as AT&T, Bosch, BP, Citi, ExxonMobil, Lockheed Martin, Merck, Novartis, Oracle, Reuters, Samsung, Tencent, UBS, Volkswagen, Yahoo, 3M & many others โ€” gain better insight, make right decisions, and improve their enterprise performance based on robust, insightful data visualization.

Whether you need to enhance your website with better reporting, embed dashboards into your on-premises and SaaS systems, or build an entirely new product, AnyChart covers all your data visualization needs. The company's products include massive out-of-the-box capabilities, combined with flexibility & simplicity.

Loved by thousands of happy customers, including more than 75% of Fortune 500 companies across all industries and over half of the top 1,000 software vendors worldwide.

In 2019, AnyChart launched a technology alliance partnership with Qlik, adding three new product extensions for Qlik Sense. The partnership enables the Qlik community to be provided with more than 30 new chart types and many valuable features natively in the Qlik environment.

PyTorch

Pricing URL
-
$ Details
Platforms
-
Release Date
-

AnyChart

$ Details
freemium $49.0 / One-off (Next Unicorn license for startups)
Platforms
JavaScript Web Qlik Windows Mac OSX Linux Android iOS TypeScript PHP Google Chrome Safari Opera Firefox Java iPhone Mobile Laravel ReactJS React Native Angular Python Node JS Cross Platform
Release Date
2003 May
Startup details
Country
United States
State
Florida
Founder(s)
Anton Baranchuk
Employees
10 - 19

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.

AnyChart features and specs

  • Chart types
    70+ (bar, line, Gantt, candlestick, waterfall, sunburst...)
  • Data formats
    Multiple (JavaScript API, XML, JSON, CSV, HTML table, Google Sheets...)
  • Integrations
    Seamlessly runs with any language, framework, and database (multiple integration templates are available)
  • Docs
    The documentation and API reference are very detailed and everything is explained in detail in a simple and clear way, with numerous readymade chart samples
  • Browser support
    Supports all browsers, including IE6+ along with mobile browsers
  • Dependencies
    None
  • Product history
    AnyChart has been operating from 2003 and the team is very experienced with a long history of releasing high-quality products.
  • Open source
    The open source code is hosted on GitHub under different licenses depending on the library
  • Flexibility
    Extremely flexible and customizable Any part of a chart can be changed and customized.
  • Interactivity
    Events can be distributed to chart elements which respond to user actions. Event listeners are simple JavaScript functions which are very easy to use and understand

Analysis of PyTorch

Overall verdict

  • Yes, PyTorch is considered a good deep learning framework.

Why this product is good

  • Ease of Use: PyTorch has an intuitive interface that makes it easier to learn and use, especially for beginners.
  • Dynamic Computation Graphs: PyTorch employs dynamic computation graphs, which provide more flexibility in building and modifying models on the fly.
  • Strong Community and Support: PyTorch has a large and active community, offering extensive resources, forums, and tutorials.
  • Research Adoption: PyTorch is widely adopted in the research community, making state-of-the-art models and techniques readily available.
  • Integration: PyTorch integrates well with other libraries and tools in the Python ecosystem, providing robust support for various applications.

Recommended for

  • Researchers and Academics: Ideal for those who need a flexible and dynamic tool for experimenting with new models and techniques.
  • Industry Practitioners: Suitable for developers and data scientists working on production-level machine learning solutions.
  • Educators and Learners: Great for educational purposes due to its easy-to-understand syntax and comprehensive documentation.

PyTorch videos

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

AnyChart videos

Heatmap Chart using AnyChart with Python

More videos:

  • Tutorial - Creating Interactive Charts with AnyChart library for Your Android App
  • Tutorial - How to Create a Gantt Chart in Qlik Sense using AnyGantt Extension by AnyChart

Category Popularity

0-100% (relative to PyTorch and AnyChart)
Data Science And Machine Learning
Data Dashboard
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Charting Libraries
0 0%
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 PyTorch and AnyChart

PyTorch Reviews

10 Python Libraries for Computer Vision
Similar to TensorFlow and Keras, PyTorch and torchvision offer powerful tools for computer vision tasks. PyTorchโ€™s dynamic computation graph and torchvisionโ€™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 Facebookโ€™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...
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...

AnyChart Reviews

  1. alairedeforest
    Fast, effective charts

    Probably the best JS chart library on the market right now.

    ๐Ÿ Competitors: CanvasJS
    ๐Ÿ‘ Pros:    Extremely simple|Fast|Affordable
    ๐Ÿ‘Ž Cons:    Not free

15 JavaScript Libraries for Creating Beautiful Charts
AnyChart is a lightweight and robust JavaScript charting library with charts designed to be embedded and integrated. AnyChart allows you to display 68 charts out-of-the-box and provides features to create your own chart types. You can save a chart as an image in PDF, PNG, JPG or SVG format.
Top 10 Visual Analytics Provider For 2021
AnyChart provides products for those who are slightly well-versed with HTML and JavaScript. Their products provide robust JavaScript charting libraries with APIs, documentation, and enterprise-grade support. Developers can integrate a variety of charts into their mobile, desktops, or web products. Their component is compatible with any database and runs on any platform....
Top 10 JavaScript Charting Libraries for Every Data Visualization Need
AnyChart is a robust, lightweight and feature-rich JS chart library with rendering in SVG/VML. It actually gives web developers a great opportunity to create any different charts that will help to make decisions based on what is seen.
Source: hackernoon.com

Social recommendations and mentions

Based on our record, PyTorch seems to be more popular. It has been mentiond 144 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.

PyTorch mentions (144)

  • Developer Take On: A High-Resolution Neural Cellular Automata
    PyTorch: A popular deep learning framework for Python. - Source: dev.to / about 1 month ago
  • Where to Get Hands-On AI Training for Cybersecurity Professionals
    Pre-configured environment. A good course ships a VM or container with Jupyter, pandas, scikit-learn, PyTorch or transformers, and realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. No setup tax. - Source: dev.to / 2 months ago
  • Running AI Models on GPU Cloud Servers: A Beginner Guide
    Install PyTorch with GPU support: Go to the official PyTorch website (pytorch.org) and use their configurator to get the correct pip or conda command for your specific CUDA version. It will look something like this:. - Source: dev.to / 3 months ago
  • Why 70% of Americans See AI as a Wealth Inequality Machine: The Developer's Role in Building Fairer Tech
    Open source contributions to democratize AI capabilities represent one of the most direct ways individual developers can impact AI inequality. Contributing to projects like Apache MXNet, PyTorch, or specialized tools for underserved communities multiplies your impact beyond individual projects. - Source: dev.to / 4 months ago
  • Nvidia's NemoClaw: The GPU-Accelerated Framework That's Revolutionizing Scientific Computing
    What's particularly intriguing is how NemoClaw integrates with Nvidia's broader AI ecosystem. Unlike standalone HPC libraries, it's designed to work seamlessly with frameworks like PyTorch and TensorFlow, enabling researchers to combine traditional numerical methods with machine learning approaches in ways that weren't practical before. - Source: dev.to / 4 months ago
View more

AnyChart mentions (0)

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

What are some alternatives?

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

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.

Chart.js - Easy, object oriented client side graphs for designers and developers.

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

Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application

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

D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.