Machine Learning & Data Science · head to head
KNIME vs BentoML
KNIME
Machine Learning & Data Science
Open source data analytics and integration platform
- From
- Free
- Rated
- -
BentoML
Machine Learning & Data Science
Build production-ready ML applications
- From
- Free
- Rated
- -
The short version
- Each has a real cost: KNIME the free Analytics Platform runs locally only, so anything shared or scheduled requires a paid Hub; BentoML core BentoML framework is Apache 2.0 and free, but the managed BentoCloud enterprise tier has no published pricing: the README instructs buyers to sign up for personal access or contact sales for enterprise use, with no rate card shown.
- They diverge on capability: KNIME covers Visual workflows, BentoML covers Model packaging.
Where they differ
Only the attributes on which KNIME and BentoML actually diverge.
Identical on both: starting price (Free), pricing model (freemium), free tier (Yes), platforms (Linux, Mac, Windows), user rating (Not yet rated), category (Machine Learning & Data Science).
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 KNIME
- Visual workflows
- Data preprocessing
- Machine learning
- Visualization
- Reporting
- Python
- R
- Spark
Only in BentoML
- Model packaging
- REST API generation
- Adaptive batching
- Multi-framework support
- Container deployment
- PyTorch
- scikit-learn
- XGBoost
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.
KNIME
- Building data pipelines and analytics workflows visually rather than in codenot BentoML
- Connecting and blending data across many sources for analysisnot BentoML
BentoML
- Machine learningnot KNIME
- Data analysisnot KNIME
- Model trainingnot KNIME
- Predictive analyticsnot KNIME
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
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
BentoML
- Core BentoML framework is Apache 2.0 and free, but the managed BentoCloud enterprise tier has no published pricing: the README instructs buyers to sign up for personal access or contact sales for enterprise use, with no rate card shown.
Pricing, plan by plan
KNIME
Free- Analytics PlatformFree
- Visual workflows
- All nodes
- Community extensions
- ServerFree
- Team collaboration
- Workflow automation
- REST API
BentoML
Free- Open SourceFree
- Model packaging
- API creation
- Local serving
- BentoCloudFree
- Managed deployment
- Auto-scaling
- Monitoring
Which should you pick?
Choose KNIME if
- You need visual workflows.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want data preprocessing.
Choose BentoML if
- You need model packaging.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want rest api generation.
Questions people ask
- Is KNIME or BentoML better?
- Neither clearly leads. KNIME starts at Free and BentoML at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, KNIME or BentoML?
- KNIME starts at Free and BentoML at Free.
- Does KNIME or BentoML run on more platforms?
- Both run on Linux, Mac, Windows, so platform support will not decide this one for you.
- Can I use KNIME for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is KNIME best used for?
- KNIME is most often used for building data pipelines and analytics workflows visually rather than in code, connecting and blending data across many sources for analysis. Of those, building data pipelines and analytics workflows visually rather than in code and connecting and blending data across many sources for analysis are not what BentoML is typically brought in for.
- What can KNIME do that BentoML cannot?
- KNIME covers Visual workflows, Data preprocessing, Machine learning, Visualization. BentoML covers Model packaging, REST API generation, Adaptive batching, Multi-framework support. Both handle TensorFlow, Linux support, Mac support, Windows support.