Software · head to head
Dataiku 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: Dataiku no pricing is published at any tier, and the plans page carries no figures at all; Comet ML the free cloud tier caps data at 25,000 spans a month with 60 day retention
- They diverge on capability: Dataiku covers Visual data prep, Comet ML covers Experiment tracking.
Where they differ
Only the attributes on which Dataiku 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 Dataiku
- Visual data prep
- AutoML
- MLOps
- Collaboration
- Governence
- Python
- R
- Spark
Only in Comet ML
- Experiment tracking
- Code versioning
- Model registry
- Hyperparameter optimization
- Production monitoring
- PyTorch
- TensorFlow
- Keras
Both cover
- Linux support
- Mac support
- Windows support
- Web support
What people use each for
The jobs each tool is most often brought in to do.
Dataiku
- Building and deploying data science and machine learning pipelinesnot Comet ML
- Giving analysts and data scientists a shared visual and code environmentnot Comet ML
Comet ML
- Tracking machine learning experiments, metrics and model versionsnot Dataiku
- Monitoring and evaluating LLM applications with tracingnot Dataiku
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Dataiku
- No pricing is published at any tier, and the plans page carries no figures at all
- User, row and compute limits are not stated, so nothing about scale can be assessed before contacting sales
- Access begins with a demo request or a trial rather than a self serve signup
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
Dataiku
Free- Free EditionFree
- Single user
- Core features
- EnterpriseFree
- Full platform
- Collaboration
- MLOps
Comet ML
Free- FreeFree
- 100 experiments
- Basic features
- Community support
- Team$179/month
- Unlimited experiments
- Team collaboration
- Priority support
Which should you pick?
Choose Dataiku if
- You need visual data prep.
- You want to start without paying.
- You work on Linux, Mac, Windows, Web.
- You also want automl.
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 Dataiku or Comet ML better?
- Neither clearly leads. Dataiku 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, Dataiku or Comet ML?
- Dataiku starts at Free and Comet ML at Free.
- Does Dataiku or Comet ML run on more platforms?
- Dataiku runs on Linux, Mac, Windows, Web. Comet ML runs on Web, Linux, Mac, Windows.
- Can I use Dataiku for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Dataiku best used for?
- Dataiku is most often used for building and deploying data science and machine learning pipelines, giving analysts and data scientists a shared visual and code environment. Of those, building and deploying data science and machine learning pipelines and giving analysts and data scientists a shared visual and code environment are not what Comet ML is typically brought in for.
- What can Dataiku do that Comet ML cannot?
- Dataiku covers Visual data prep, AutoML, MLOps, Collaboration. Comet ML covers Experiment tracking, Code versioning, Model registry, Hyperparameter optimization. Both handle Linux support, Mac support, Windows support, Web support.