ClearML manages AI experiments, data, pipelines, orchestration, scheduling, and model serving in one MLOps platform.
Open source
24 alternativesCascade
Cascade supports MLOps workflows for smaller projects without a full platform.
About Cascade
Cascade is an open-source Python library for MLOps in smaller projects. It tracks experiments, datasets, models, and artifacts locally on the filesystem. According to its README, it needs no tracking server, cloud account, or complex infrastructure, and it is listed in the Model Lifecycle section of the Awesome MLOps list.
Cascade stores models with their metrics, parameters, tags, descriptions, and metadata, and groups them into repositories and lines. Dataset wrappers record each data processing stage, so data transforms can be versioned alongside model experiments. An optional separate package, cascade-ui, provides a visual dashboard for Cascade experiments.
Key features
- Local experiment tracking with Python and the filesystem, without a tracking server
- Saving and restoring models with metadata, metrics, parameters, tags, and descriptions
- Repository and line structure that groups experiments on one model type
- Dataset wrappers that record data transformation stages in metadata
- Optional cascade-ui package that adds a visual dashboard for experiments
- Cascade Recipes, a growing set of project templates such as baseline sweeps and data lineage
Best for: Python developers working on smaller ML projects who want experiment tracking without a full MLOps platform or cloud setup.
Good for
- Runs locally and, per the README, does not require a cloud account or tracking server
- Open source and installable with pip
- Covers experiments, datasets, and models in one library
Watch out for
- The visual dashboard is a separate project that must be installed on its own
- The README describes local, filesystem-based tracking and does not describe shared or server-based team use
- Cascade Recipes is described as a growing collection, so coverage of use cases is still expanding
Cascade at a glance
- Website
- github.com/Oxid15/cascade
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Cascade FAQ
Does Cascade require a cloud account or tracking server?
No. The README states that Cascade tracks experiments locally with Python and the filesystem and does not require a tracking server, cloud account, or complex infrastructure.
How can I view experiments in a visual interface?
Install the separate cascade-ui package with pip install cascade-ui, then run cascade ui to open a dashboard for your experiments.
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