Software · head to head
DVC vs Azure Machine Learning
Azure Machine Learning
Software
Enterprise-grade machine learning service
- From
- Free
- Rated
- -
The short version
- Each has a real cost: DVC dVC is Apache 2.0 licensed open source with no enterprise tier or paid support offering documented in the project itself; teams needing SLA-backed support get nothing from the DVC project directly.; Azure Machine Learning requires knowledge of Azure ecosystem and integration with other Azure services
- They diverge on capability: DVC covers Data versioning, Azure Machine Learning covers Automated ML.
Where they differ
Only the attributes on which DVC and Azure Machine Learning actually diverge.
| Attribute | DVC | Azure Machine Learning |
|---|---|---|
| Pricing model | open-source | usage-based |
| Platforms | Linux, Mac, Windows | Azure Cloud |
| Founded | 2018 | 1975 |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Unknown).
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 DVC
- Data versioning
- Pipeline management
- Experiment tracking
- Remote storage
- Git integration
- Git
- S3
- Azure Blob
Only in Azure Machine Learning
- Automated ML
- Designer (drag-and-drop)
- Notebooks
- MLOps
- Model registry
- Azure Blob Storage
- Azure DevOps
- Power BI
What people use each for
The jobs each tool is most often brought in to do.
DVC
- Machine learning
- Data analysis
- Model training
- Predictive analytics
Azure Machine Learning
- Machine learning
- Data analysis
- Model training
- Predictive analytics
Both are used for machine learning, data analysis, model training, predictive analytics, on those jobs the choice comes down to price and fit rather than capability.
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
DVC
- DVC is Apache 2.0 licensed open source with no enterprise tier or paid support offering documented in the project itself; teams needing SLA-backed support get nothing from the DVC project directly.
Azure Machine Learning
- Requires knowledge of Azure ecosystem and integration with other Azure services
- Compute resources for training and inference generate separate charges
Pricing, plan by plan
DVC
Free- Open SourceFree
- Data versioning
- Pipeline management
- Experiment tracking
- DVC StudioFree
- Web UI
- Team collaboration
- Visualizations
Azure Machine Learning
Free- Free TierFree
- Limited compute
- Basic features
- Pay-as-you-go$0.05/hour
- Full platform
- All compute options
- Enterprise features
Which should you pick?
Choose DVC if
- You need data versioning.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want pipeline management.
Choose Azure Machine Learning if
- You need automated ml.
- You want to start without paying.
- You work on Azure Cloud.
- You also want designer (drag-and-drop).
Questions people ask
- Is DVC or Azure Machine Learning better?
- Neither clearly leads. DVC starts at Free and Azure Machine Learning at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, DVC or Azure Machine Learning?
- DVC starts at Free and Azure Machine Learning at Free.
- Does DVC or Azure Machine Learning run on more platforms?
- DVC runs on Linux, Mac, Windows. Azure Machine Learning runs on Azure Cloud.
- Can I use DVC for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is DVC best used for?
- DVC is most often used for machine learning, data analysis, model training, predictive analytics.
- What can DVC do that Azure Machine Learning cannot?
- DVC covers Data versioning, Pipeline management, Experiment tracking, Remote storage. Azure Machine Learning covers Automated ML, Designer (drag-and-drop), Notebooks, MLOps.
Answered from the vendors’ own pages
Azure Machine Learning: Does Azure Machine Learning have any platform licensing fees?
No, Azure Machine Learning carries no extra cost. You only pay for the underlying compute resources utilized during model training or inference.
SourceAzure Machine Learning: What AutoML capabilities does Azure Machine Learning provide?
Azure Machine Learning supports automated model creation for classification, regression, vision, and natural language processing tasks.
SourceAzure Machine Learning: Does Azure ML support language model fine-tuning?
Yes, Azure Machine Learning supports fine-tuning of foundation models from providers including OpenAI, Meta, Hugging Face, and Cohere.
SourceAzure Machine Learning: What MLOps features are included?
Azure ML includes end-to-end pipeline automation with CI/CD capabilities, managed endpoints for model deployment, and monitoring tools.
SourceAzure Machine Learning: Can I access foundation models from multiple vendors?
Yes, Azure Machine Learning provides access to a model catalog with foundation models from Microsoft, OpenAI, Hugging Face, Meta, and Cohere.
Source