Machine Learning · head to head
Keras vs Mathesar
Mathesar
Spreadsheets
Spreadsheet style interface that edits an existing PostgreSQL database directly, with no schema of its own
- 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; Mathesar there is no hosted offering of any kind, so a team without someone who can run and secure a server cannot use it at all.
- They diverge on capability: Keras covers Sequential and Functional API, Mathesar covers Direct PostgreSQL editing.
- Prices and features above were last checked on 31 August 2026.
Where they differ
Only the attributes on which Keras and Mathesar 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 Mathesar
- Direct PostgreSQL editing
- PostgreSQL permissions
- Schema editing
- Data exploration
- Relationship navigation
- Import of tabular files
- Self hosted only
What people use each for
The jobs each tool is most often brought in to do.
Keras
- Machine learningnot Mathesar
- Data analysisnot Mathesar
- Model trainingnot Mathesar
- Predictive analyticsnot Mathesar
Mathesar
- A nonprofit or research group whose data is already in PostgreSQL and whose staff cannot write SQLnot Keras
- Giving analysts a safe editing interface governed by database roles that already existnot Keras
- Replacing a hand built Django or Rails admin screen that nobody wants to maintainnot Keras
- Editing production reference data where an export, edit and reimport cycle would risk losing concurrent changesnot 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
Mathesar
- There is no hosted offering of any kind, so a team without someone who can run and secure a server cannot use it at all.
- It works only with PostgreSQL, so a MySQL, SQL Server or SQLite estate is excluded outright.
- There are no automations, no webhooks and effectively no integration catalogue, so it edits data and does nothing else.
- Because it writes to the live database, a careless bulk edit or column type change is a production change with no staging step and no undo.
- Development is grant and community funded rather than commercially funded, so roadmap pace and long term continuity carry a different risk profile from a venture backed vendor.
Pricing, plan by plan
Keras
Free- Open SourceFree
- High-level API
- Pre-built layers
- Model serialization
Mathesar
Free- Self hosted open sourceFree
- No licence fee
- No hosted option offered
- Connects to your existing PostgreSQL database
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 Mathesar if
- You need direct postgresql editing.
- You want to start without paying.
- You work on Web, Linux.
- You also want postgresql permissions.
Questions people ask
- Is Keras or Mathesar better?
- Neither clearly leads. Keras starts at Free and Mathesar at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Keras or Mathesar?
- Keras starts at Free and Mathesar at Free.
- Does Keras or Mathesar run on more platforms?
- Keras runs on Python, Google Colab, Jupyter. Mathesar runs on Web, Linux.
- 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 Mathesar is typically brought in for.
- What can Keras do that Mathesar cannot?
- Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning. Mathesar covers Direct PostgreSQL editing, PostgreSQL permissions, Schema editing, Data exploration.
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.
SourceMathesar: Is there a cloud version?
No. Self hosting is the only option, and that is a deliberate project decision rather than a gap waiting to be filled.
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.
SourceMathesar: How does it handle permissions?
Through PostgreSQL roles and privileges directly, so there is no second permission model to keep in step.
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.
SourceMathesar: What is the row limit?
Whatever PostgreSQL can handle. Mathesar adds no storage layer of its own.
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.
SourceMathesar: Does it support databases other than PostgreSQL?
No.
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.
SourceMathesar: Can it replace Airtable?
Only for editing and exploring data. There are no automations, apps or integrations.
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