Machine Learning · head to head
Keras vs KNIME

KNIME
Machine Learning
Open source data analytics and integration platform
- 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; KNIME the free Analytics Platform runs locally only, so anything shared or scheduled requires a paid Hub
- They diverge on capability: Keras covers Sequential and Functional API, KNIME covers Visual workflows.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Keras and KNIME actually diverge.
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning).
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
- JAX
- PyTorch
Only in KNIME
- Visual workflows
- Data preprocessing
- Machine learning
- Visualization
- Reporting
- Python
- R
- Spark
Both cover
- TensorFlow
- Linux support
- Mac support
- Windows support
What people use each for
The jobs each tool is most often brought in to do.
Keras
- Machine learningnot KNIME
- Data analysisnot KNIME
- Model trainingnot KNIME
- Predictive analyticsnot KNIME
KNIME
- Data science and machine learning workflowsnot Keras
- ETL and data pipeline automationnot Keras
- Predictive analytics and modelingnot 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
KNIME
- The free Analytics Platform runs locally only, so anything shared or scheduled requires a paid Hub
- The free AI assistant is limited to 20 interactions a month
- Paid workflow runtime is metered in credits, with 120 included on Pro and overage at $0.025 per vCore minute
- The Team plan at $99 a month includes 3 members, with additional seats at $49 a month each
- Business Hub pricing is on request, and its tiers are capped at 4, 8 and 16 vCores with 5, 5 and 20 users
Pricing, plan by plan
Keras
Free- Open SourceFree
- High-level API
- Pre-built layers
- Model serialization
KNIME
Free- Analytics PlatformFree
- 300+ data sources
- Unlimited local processing
- K-AI assistant (20 interactions/month)
- Pro$19/month
- 120 workflow runtime credits
- Data app deployment
- K-AI (500 interactions/month)
- Team$99/month
- All Pro features
- Collaboration spaces for up to 3 team members
- Additional members: $49/month each
- Business Hub$null/month
- Enterprise automation and governance
- LDAP/OAuth authentication
- Staged deployment
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 KNIME if
- You need visual workflows.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want data preprocessing.
Questions people ask
- Is Keras or KNIME better?
- Neither clearly leads. Keras starts at Free and KNIME at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Keras or KNIME?
- Keras starts at Free and KNIME at Free.
- Does Keras or KNIME run on more platforms?
- Keras runs on Python, Google Colab, Jupyter. KNIME runs on Linux, Mac, Windows.
- 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 KNIME is typically brought in for.
- What can Keras do that KNIME cannot?
- Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning. KNIME covers Visual workflows, Data preprocessing, Machine learning, Visualization. Both handle TensorFlow, Linux support, Mac support, Windows support.
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.
SourceKNIME: Is KNIME free?
Yes, KNIME Analytics Platform is free with 300+ data sources, unlimited local processing, and 20 K-AI assistant interactions per month.
SourceKeras: 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.
SourceKNIME: What do KNIME paid plans cost?
Pro plan starts at $19/month with 120 runtime credits. Team plan starts at $99/month for up to 3 members, with additional members at $49/month each.
SourceKeras: 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.
SourceKNIME: What is KNIME's runtime credit system?
Pro and Team plans include runtime credits for workflow execution. Additional runtime beyond included credits costs $0.025 per vCore minute.
SourceKeras: 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.
SourceKNIME: Does KNIME offer enterprise pricing?
Yes, Business Hub is available for enterprises needing automation, governance, LDAP/OAuth auth, and dedicated resources. Pricing available on request.
SourceKeras: 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.
SourceRelated pages
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