Canonical MLOps
5.4#23 in mlops platformsWebLinuxSelf-hosted
VisitCanonical MLOps vs Databricks Notebooks
Databricks Notebooks
8.7#1 in business intelligence toolsFree planFree planAndroidWebAPILinux
VisitWhat both publish
| Fact | Canonical MLOps | Databricks Notebooks |
|---|---|---|
| Founded | 2004 | 2013 |
| Headquarters | London, United Kingdom | San Francisco, California, United States |
| Integrations | Canonical lists Jupyter, Grafana, and Prometheus as tools to use with Charmed MLflow. | Databricks offers native cloud integrations for AWS, Azure and Google Cloud, including marketplace or console deployment paths. |
Canonical MLOps plans
- Canonical MLOps support subscription—
Databricks Notebooks plans
- Free EditionFree
- Pay as you go—
- Pay as you goPriced on request
- Committed Use Contracts—
- Committed Use ContractsPriced on request
- Free EditionFree
Pick Canonical MLOps if…
It suits teams running machine-learning workflows across Linux, self-hosted environments, or the web. It is also relevant for organisations needing experiment tracking, model registries, orchestration, serving, and cloud Kubernetes support.
Pick Databricks Notebooks if…
It suits data and machine-learning teams that need notebooks alongside SQL analytics, streaming, governance, lineage, or model workflows. The free edition can suit a user who can work within one serverless workspace and limited compute size and usage.