Software · head to head
KNIME vs Comet ML
Comet ML
Software
Platform for tracking, comparing, and optimizing ML experiments
- 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; Comet ML the free cloud tier caps data at 25,000 spans a month with 60 day retention
- They diverge on capability: KNIME covers Visual workflows, Comet ML covers Experiment tracking.
Where they differ
Only the attributes on which KNIME and Comet ML actually diverge.
Identical on both: starting price (Free), pricing model (freemium), free tier (Yes), user rating (Not yet rated), category (Unknown).
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 Comet ML
- Experiment tracking
- Code versioning
- Model registry
- Hyperparameter optimization
- Production monitoring
- PyTorch
- Keras
- scikit-learn
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 Comet ML
- Connecting and blending data across many sources for analysisnot Comet ML
Comet ML
- Tracking machine learning experiments, metrics and model versionsnot KNIME
- Monitoring and evaluating LLM applications with tracingnot 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
Comet ML
- The free cloud tier caps data at 25,000 spans a month with 60 day retention
- Retention stays at 60 days even on the paid Pro plan, and extending it is a $29 per 100k spans add on
- Overage on Pro is $5 per additional 100,000 spans
- The free MLOps tier is a single user with 100 GB of storage and training hours governed by a fair usage policy
- Pro MLOps is $19 per user per month and caps the team at 10 users
Pricing, plan by plan
KNIME
Free- Analytics PlatformFree
- Visual workflows
- All nodes
- Community extensions
- ServerFree
- Team collaboration
- Workflow automation
- REST API
Comet ML
Free- FreeFree
- 100 experiments
- Basic features
- Community support
- Team$179/month
- Unlimited experiments
- Team collaboration
- Priority support
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 Comet ML if
- You need experiment tracking.
- You want to start without paying.
- You work on Web, Linux, Mac, Windows.
- You also want code versioning.
Questions people ask
- Is KNIME or Comet ML better?
- Neither clearly leads. KNIME starts at Free and Comet ML at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, KNIME or Comet ML?
- KNIME starts at Free and Comet ML at Free.
- Does KNIME or Comet ML run on more platforms?
- KNIME runs on Linux, Mac, Windows. Comet ML runs on Web, Linux, Mac, Windows.
- 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 Comet ML is typically brought in for.
- What can KNIME do that Comet ML cannot?
- KNIME covers Visual workflows, Data preprocessing, Machine learning, Visualization. Comet ML covers Experiment tracking, Code versioning, Model registry, Hyperparameter optimization. Both handle TensorFlow, Linux support, Mac support, Windows support.