Machine Learning & Data Science · head to head
Comet ML vs Pachyderm

Comet ML
Machine Learning & Data Science
Platform for tracking, comparing, and optimizing ML experiments
- From
- Free
- Rated
- -
P
Pachyderm
Machine Learning & Data Science
Data versioning and pipelines for production ML
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Comet ML the free cloud tier caps data at 25,000 spans a month with 60 day retention; Pachyderm core software is Apache-2.0 licensed and free to self-host
- They diverge on capability: Comet ML covers Experiment tracking, Pachyderm covers Data versioning.
Where they differ
Only the attributes on which Comet ML and Pachyderm actually diverge.
Identical on both: starting price (Free), pricing model (freemium), free tier (Yes), 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 Comet ML
- Experiment tracking
- Code versioning
- Model registry
- Hyperparameter optimization
- Production monitoring
- PyTorch
- TensorFlow
- Keras
Only in Pachyderm
- Data versioning
- Data-driven pipelines
- Automatic provenance
- Kubernetes-native
- Reproducibility
- Kubernetes
- S3
- GCS
Both cover
- Linux support
What people use each for
The jobs each tool is most often brought in to do.
Comet ML
- Tracking machine learning experiments, metrics and model versionsnot Pachyderm
- Monitoring and evaluating LLM applications with tracingnot Pachyderm
Pachyderm
- Machine learningnot Comet ML
- Data analysisnot Comet ML
- Model trainingnot Comet ML
- Predictive analyticsnot Comet ML
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
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
Pachyderm
- Core software is Apache-2.0 licensed and free to self-host
Pricing, plan by plan
Comet ML
Free- FreeFree
- 100 experiments
- Basic features
- Community support
- Team$179/month
- Unlimited experiments
- Team collaboration
- Priority support
Pachyderm
Free- CommunityFree
- Core features
- Community support
- EnterpriseFree
- Advanced security
- Premium support
- SLAs
Which should you pick?
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.
Choose Pachyderm if
- You need data versioning.
- You want to start without paying.
- You work on Linux.
- You also want data-driven pipelines.
Questions people ask
- Is Comet ML or Pachyderm better?
- Neither clearly leads. Comet ML starts at Free and Pachyderm at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Comet ML or Pachyderm?
- Comet ML starts at Free and Pachyderm at Free.
- Does Comet ML or Pachyderm run on more platforms?
- Comet ML runs on Web, Linux, Mac, Windows. Pachyderm runs on Linux.
- Can I use Comet ML for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Comet ML best used for?
- Comet ML is most often used for tracking machine learning experiments, metrics and model versions, monitoring and evaluating llm applications with tracing. Of those, tracking machine learning experiments, metrics and model versions and monitoring and evaluating llm applications with tracing are not what Pachyderm is typically brought in for.
- What can Comet ML do that Pachyderm cannot?
- Comet ML covers Experiment tracking, Code versioning, Model registry, Hyperparameter optimization. Pachyderm covers Data versioning, Data-driven pipelines, Automatic provenance, Kubernetes-native. Both handle Linux support.
Related pages
Other head to heads
- Comet ML vs AWS SageMaker
- Comet ML vs Google Vertex AI
- Comet ML vs Azure Machine Learning
- Comet ML vs DataRobot
- Comet ML vs Snowflake
- Comet ML vs TensorFlow
- Comet ML vs Keras
- Comet ML vs MLflow
- Comet ML vs Jupyter
- Comet ML vs PyTorch
- Comet ML vs scikit-learn
- Comet ML vs Apache Spark MLlib
- Comet ML vs Weights & Biases
- Comet ML vs Alteryx
- Comet ML vs Anaconda
- Comet ML vs Databricks
- Comet ML vs Dataiku
- Comet ML vs DVC
- Pachyderm vs AWS SageMaker
- Pachyderm vs Google Vertex AI
- Pachyderm vs Azure Machine Learning
- Pachyderm vs DataRobot
- Pachyderm vs Snowflake
- Pachyderm vs TensorFlow
- Pachyderm vs Keras
- Pachyderm vs MLflow
- Pachyderm vs Jupyter
- Pachyderm vs PyTorch
- Pachyderm vs scikit-learn
- Pachyderm vs Apache Spark MLlib
- Pachyderm vs Weights & Biases
- Pachyderm vs Alteryx
- Pachyderm vs Anaconda
- Pachyderm vs Databricks
- Pachyderm vs Dataiku
- Pachyderm vs DVC
