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Spreadsheets · head to head

APITable vs Keras

APITable logo

APITable

Spreadsheets

Open source spreadsheet database with an API first design and an embeddable widget system

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: APITable records are held in the product own schema rather than as native database tables, so the practical row ceiling is a product limit and large tables should be load tested before commitment.; Keras limited customization compared to TensorFlow; advanced users may find constraints in complex model designs
  • They diverge on capability: APITable covers API first design, Keras covers Sequential and Functional API.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which APITable and Keras actually diverge.

Attributes where APITable and Keras differ
AttributeAPITableKeras
Pricing modelOpen source, no licence feeopen-source
PlatformsWeb, LinuxPython, Google Colab, Jupyter
CategorySpreadsheetsMachine Learning
FoundedUnknown2015

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 APITable

  • API first design
  • Widget SDK
  • Embeddable views
  • Multiple view types
  • Linked records and formulas
  • Self hosting
  • Real time collaboration

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.

APITable

  • Embedding an editable table view inside a product you are building, rather than sending users to another toolnot Keras
  • An internal platform where tables are read and written mostly by code through the API and only occasionally by peoplenot Keras
  • A self hosted replacement for a per seat spreadsheet database where seat count is the cost drivernot Keras
  • Building a custom dashboard widget that sits beside the data instead of in a separate reporting toolnot Keras

Keras

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

Where each one falls short

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

APITable

  • Records are held in the product own schema rather than as native database tables, so the practical row ceiling is a product limit and large tables should be load tested before commitment.
  • The hosted free tier caps records per space, so evaluating on the cloud version gives a misleading picture of what the software can do when self hosted.
  • Automation is thin compared with the commercial alternatives, and most real workflows end up in an external automation tool.
  • The self hosted deployment is heavier than a single container, so running it properly means managing several services rather than one.
  • Documentation and community activity are uneven in English, and finding an answer to an operational problem can take longer than the problem itself deserves.

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

APITable

Free
  • Self hosted open sourceFree
    • No licence fee
    • No product record cap on self hosted deployments
    • Docker and Kubernetes deployment

Keras

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

Which should you pick?

Choose APITable if

  • You need api first design.
  • You want to start without paying.
  • You work on Web, Linux.
  • You also want widget sdk.
APITable 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 APITable or Keras better?
Neither clearly leads. APITable 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, APITable or Keras?
APITable starts at Free and Keras at Free.
Does APITable or Keras run on more platforms?
APITable runs on Web, Linux. Keras runs on Python, Google Colab, Jupyter.
Can I use APITable for free?
Both have a free tier, so you can try either at no cost before committing.
What is APITable best used for?
APITable is most often used for embedding an editable table view inside a product you are building, rather than sending users to another tool, an internal platform where tables are read and written mostly by code through the api and only occasionally by people, a self hosted replacement for a per seat spreadsheet database where seat count is the cost driver, building a custom dashboard widget that sits beside the data instead of in a separate reporting tool. Of those, embedding an editable table view inside a product you are building, rather than sending users to another tool and an internal platform where tables are read and written mostly by code through the api and only occasionally by people are not what Keras is typically brought in for.
What can APITable do that Keras cannot?
APITable covers API first design, Widget SDK, Embeddable views, Multiple view types. Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning.

Answered from the vendors’ own pages

APITable: What is the record limit?

The self hosted edition has no product cap, but performance is bounded by the internal schema rather than by your database. Test at your expected size.

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
APITable: Can I embed it in my own product?

Yes, and that is the main reason to choose it. Views embed and the widget SDK extends them.

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
APITable: Is the hosted version representative?

No. Its free tier caps records per space, which is a commercial limit rather than a technical one.

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
APITable: How hard is self hosting?

Harder than a single container. Plan for several services and someone to keep them running.

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
APITable: Does it do automations?

Lightly. Expect to pair it with an external automation tool for anything multi step.

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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