Machine Learning · head to head
Keras vs Rowy
Rowy
Spreadsheets
Spreadsheet interface for Google Cloud Firestore with cloud functions written in the browser
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Keras limited customization compared to TensorFlow; advanced users may find constraints in complex model designs; Rowy every Firestore limit is inherited, including the one megabyte per document ceiling and roughly one sustained write per second per document, which surprises users who expect spreadsheet behaviour.
- They diverge on capability: Keras covers Sequential and Functional API, Rowy covers Firestore backed grid.
- Prices and features above were last checked on 31 August 2026.
Where they differ
Only the attributes on which Keras and Rowy actually diverge.
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 Keras
- Sequential and Functional API
- Pre-built neural network layers
- Model training and evaluation
- Transfer learning
- Model serialization
- TensorFlow
- JAX
- PyTorch
Only in Rowy
- Firestore backed grid
- Browser authored cloud functions
- Typed columns
- Runs in your Google Cloud project
- Role based access
- Form view
- Open source
What people use each for
The jobs each tool is most often brought in to do.
Keras
- Machine learningnot Rowy
- Data analysisnot Rowy
- Model trainingnot Rowy
- Predictive analyticsnot Rowy
Rowy
- A Firebase application that needs an internal admin interface without building onenot Keras
- Operations staff correcting production records in Firestore without developer involvementnot Keras
- Attaching a small transformation or notification function to a field change without a full deployment pipelinenot Keras
- A content team populating documents that a mobile application reads directly from Firestorenot Keras
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
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
Rowy
- Every Firestore limit is inherited, including the one megabyte per document ceiling and roughly one sustained write per second per document, which surprises users who expect spreadsheet behaviour.
- Firestore has no joins, so linking tables in the grid is a convenience layer rather than a relational feature and reports across collections still need a separate query.
- It is useful only to teams already on Firebase, so choosing it effectively locks the operational tooling to one cloud vendor.
- Query costs are billed by document read, and an unfiltered grid on a large collection can generate a bill that a spreadsheet user has no intuition for.
- Development activity has slowed relative to the broader category, so evaluate current maintenance before making it load bearing for internal operations.
Pricing, plan by plan
Keras
Free- Open SourceFree
- High-level API
- Pre-built layers
- Model serialization
Rowy
Free- Open source self hostedFree
- No licence fee
- Deploys into your own Google Cloud project
- You pay Google Cloud for Firestore reads, writes and storage
Which should you pick?
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.
Choose Rowy if
- You need firestore backed grid.
- You want to start without paying.
- You also want browser authored cloud functions.
Questions people ask
- Is Keras or Rowy better?
- Neither clearly leads. Keras starts at Free and Rowy at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Keras or Rowy?
- Keras starts at Free and Rowy at Free.
- Does Keras or Rowy run on more platforms?
- Keras runs on Python, Google Colab, Jupyter. Rowy runs on Web.
- Can I use Keras for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Keras best used for?
- Keras is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Rowy is typically brought in for.
- What can Keras do that Rowy cannot?
- Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning. Rowy covers Firestore backed grid, Browser authored cloud functions, Typed columns, Runs in your Google Cloud project.
Answered from the vendors’ own pages
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.
SourceRowy: Where is my data stored?
In your own Firestore instance inside your own Google Cloud project. Rowy does not hold a copy.
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.
SourceRowy: What does it cost to run?
No licence fee. You pay Google Cloud for Firestore reads, writes, storage and function invocations, and an open grid on a big collection reads a lot.
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.
SourceRowy: Can it do joins across collections?
Not really. Firestore does not support joins, and no interface layer can add them.
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.
SourceRowy: Is there a row limit?
Not from Rowy. The limits that bite are Firestore document size and per document write throughput.
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.
SourceRowy: Is it suitable if I am not on Firebase?
No. It is specifically a Firestore interface.
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