Side by side
mlop vs Rubicon-ML
Both stand on ml experiment tracking software. Which one you can start free with, which one lets you read the code, and what each costs once you pay.
Free plan Self-hostedWeb
Choose mlop if you want experiment tracking with real-time monitoring and a Free plan for one seat. Teams needing more seats, storage, a self-hosted option, or Enterprise support can review its paid tiers, but their prices are available only by discussion.
Visit mlop Free plan APILinuxSelf-hosted+1
Rubicon-ML provides experiment logging, storage choices, and review tools in a Python package that can work without a hosted server. Users considering its Weights & Biases backend should account for the documented missing capabilities.
Visit Rubicon-MLThe facts
| mlop | Rubicon-ML | |
|---|---|---|
| Free plan | Yes | Yes |
| Open source | Not published | Not published |
| Runs on | Self-hosted, Web | API, Linux, Self-hosted, Web |
| Lowest paid plan | Free or on request | Free or on request |
| Plans published | 3 | 1 |
| Maker | Not published | Not published |
| Website | mlop.ai | capitalone.github.io |
| On ml experiment tracking software | #16 of 39 | #12 of 39 |
mlop: what it does well
- Tracks experiments, model versions, hyperparameters, metrics, artifacts, and gradients.
- Real-time monitoring and experiment comparison views are documented.
- Can alert users to poor training performance and suggest responses.
- Tracks experiment versions and uncommitted files in real time.
- Free plan includes unlimited logging hours and 10 GB storage.
What to know first
- Free plan is limited to one seat and 10 GB of storage.
- Compute is labeled Private Beta, and Inference is Coming Soon.
Rubicon-ML: what it does well
- Records inputs, outputs, parameters, and outcomes.
- Connects experiments with Git branch and commit details.
- Supports local filesystem, S3, and in-memory storage.
- Integrates with Prefect and Scikit-learn.
- Logs experiments in parallel.
What to know first
- Weights & Biases backend is experimental.
- W&B lacks project-level artifacts and dataframes.
- Visualization tools are an optional pip extra.
Alternatives to mlop Alternatives to Rubicon-ML The whole list