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Django vs Keras

Django logo

Django

Web Development

The web framework for perfectionists with deadlines

From
Free
Rated
-
Full reviewWebsite
Keras logo

Keras

Machine Learning

Deep learning API for humans

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Django does not fully support asynchronous database access; Keras limited customization compared to TensorFlow; advanced users may find constraints in complex model designs
  • They diverge on capability: Django covers Model-View-Template (MVT), Keras covers Sequential and Functional API.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Django and Keras actually diverge.

Attributes where Django and Keras differ
AttributeDjangoKeras
Pricing modelfreeopen-source
PlatformsLinux, macOS, WindowsPython, Google Colab, Jupyter
CategoryWeb DevelopmentMachine Learning
Founded20052015

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Django

  • Model-View-Template (MVT)
  • Object-relational mapping
  • Automatic admin interface
  • URL routing
  • Template engine
  • Form handling
  • Authentication system
  • Internationalization

Only in Keras

  • Sequential and Functional API
  • Pre-built neural network layers
  • Model training and evaluation
  • Transfer learning
  • Model serialization
  • TensorFlow
  • JAX
  • PyTorch

What people use each for

The jobs each tool is most often brought in to do.

Django

  • Web application developmentnot Keras
  • Content management systemsnot Keras
  • E-commerce platformsnot Keras
  • API developmentnot Keras
  • News websitesnot Keras
  • Social networksnot Keras

Keras

  • Machine learningnot Django
  • Data analysisnot Django
  • Model trainingnot Django
  • Predictive analyticsnot Django

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Django

  • Does not fully support asynchronous database access
  • Monolithic design can feel restrictive for small-scale or lightweight applications
  • Batteries-included approach adds overhead if features are not needed
  • Slower framework evolution due to backward compatibility requirements

Keras

  • Limited customization compared to TensorFlow; advanced users may find constraints in complex model designs
  • Error messages can be vague and unhelpful, making debugging challenging
  • Smaller ecosystem and fewer pre-trained models than TensorFlow or PyTorch

Pricing, plan by plan

Django

Free
  • Open SourceFree
    • Full web framework
    • Admin interface
    • ORM system

Keras

Free
  • Open SourceFree
    • High-level API
    • Pre-built layers
    • Model serialization

Which should you pick?

Choose Django if

  • You need model-view-template (mvt).
  • You want to start without paying.
  • You work on Linux, macOS, Windows.
  • You also want object-relational mapping.
Django review

Choose Keras if

  • You need sequential and functional api.
  • You want to start without paying.
  • You work on Python, Google Colab, Jupyter.
  • You also want pre-built neural network layers.
Keras review

Questions people ask

Is Django or Keras better?
Neither clearly leads. Django starts at Free and Keras at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Django or Keras?
Django starts at Free and Keras at Free.
Does Django or Keras run on more platforms?
Django runs on Linux, macOS, Windows. Keras runs on Python, Google Colab, Jupyter.
Can I use Django for free?
Both have a free tier, so you can try either at no cost before committing.
What is Django best used for?
Django is most often used for web application development, content management systems, e-commerce platforms, api development. Of those, web application development and content management systems are not what Keras is typically brought in for.
What can Django do that Keras cannot?
Django covers Model-View-Template (MVT), Object-relational mapping, Automatic admin interface, URL routing. Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning.

Answered from the vendors’ own pages

Django: What databases does Django support?

Django natively supports PostgreSQL, MySQL, SQLite3, and Oracle databases through its ORM, allowing developers to switch databases without rewriting code.

Source
Keras: What is Keras?

Keras is a high-level deep learning API built on top of TensorFlow that simplifies building and training neural networks. Keras 3 supports multiple backends including TensorFlow, PyTorch, and JAX, making it backend-agnostic.

Source
Django: How does Django handle database schema changes?

Django includes a built-in migration system. Developers use makemigrations to create migration files and migrate to apply changes to the database schema.

Source
Keras: What model architectures does Keras support?

Keras supports the Sequential model for linear stacks of layers, the Functional API for arbitrary graph architectures, and model subclassing for custom implementations. All approaches provide access to layers, optimizers, metrics, and callbacks.

Source
Django: Does Django support asynchronous programming?

Django added basic async/await support, but full asynchronous database access remains limited. The framework does not fully support asynchronous programming, which can be a limitation for real-time applications.

Source
Keras: Can Keras models run on TPUs and GPUs?

Yes, Keras models can run on TPU Pods or large GPU clusters, be exported to run in browsers or on mobile devices, and be served via web APIs.

Source
Django: Is Django free and open source?

Yes, Django is free and open-source software maintained by the Django Software Foundation, founded in June 2008.

Source
Keras: Does Keras offer pre-trained models?

Yes, Keras provides pre-trained models through KerasHub and Keras Applications for common deep learning tasks like image classification, object detection, and NLP.

Source
Keras: Who should use Keras?

Keras is ideal for beginners and rapid prototyping due to its simplicity and user-friendly interface. Advanced users and production deployments may benefit more from lower-level frameworks like TensorFlow or PyTorch for greater customization.

Source
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