Metaflow
7.5#4 in ml experiment tracking softwareFree planFree planWebAPILinuxmacOS
VisitMetaflow vs Rubicon-ML
Rubicon-ML
6.5#10 in ml experiment tracking softwareFree planFree planWebAPILinuxSelf-hosted
VisitWhat both publish
| Fact | Metaflow | Rubicon-ML |
|---|---|---|
| Installation | The package is installed with pip, and conda-forge installation is also documented. | The Python package can be installed using pip or conda-forge. |
| Integrations | Documented integrations include AWS Batch, AWS Step Functions, Kubernetes, Argo Workflows, and Apache Airflow. | The documentation includes integrations for Git, Prefect, and Scikit-learn. |
| Intended users | Metaflow is aimed at data scientists and ML/AI engineers; its documentation says it offers little benefit for small notebook experiments with no scaling, criticality, or complexity needs. | The package metadata identifies developers and science or research users as its intended audience. |
Metaflow plans
- Open-source MetaflowFree
Rubicon-ML plans
- rubicon-mlFree
Pick Metaflow if…
Metaflow is suited to data scientists and ML or AI engineers building workflows that may need scaling. It is less useful for simple notebook experiments without scaling or operational complexity needs.
Pick Rubicon-ML if…
Rubicon-ML suits developers and science or research users who want to log and review model experiments. It may fit teams that need Git-linked records and pluggable storage choices.