Machine Learning & Data Science · head to head
DVC vs Orange

DVC
Machine Learning & Data Science
Data version control for machine learning projects
- From
- Free
- Rated
- -

Orange
Machine Learning & Data Science
Data mining and visualization toolkit
- 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.; Orange orange is licensed under the GNU General Public License version 3, so distributing modified or derived software requires releasing the source under the GPL
- They diverge on capability: DVC covers Data versioning, Orange covers Visual programming.
Where they differ
Only the attributes on which DVC and Orange actually diverge.
Identical on both: starting price (Free), pricing model (open-source), free tier (Yes), platforms (Linux, Mac, Windows), user rating (Not yet rated), category (Machine Learning & Data Science).
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 Orange
- Visual programming
- Data visualization
- Machine learning
- Text mining
- Bioinformatics
- Python
- scikit-learn
- PyQt
Both cover
- Linux support
- Mac support
- Windows support
What people use each for
The jobs each tool is most often brought in to do.
DVC
- Machine learningnot Orange
- Data analysisnot Orange
- Model trainingnot Orange
- Predictive analyticsnot Orange
Orange
- Visual programming for data mining and machine learning workflowsnot DVC
- Teaching data science without writing codenot DVC
- Exploratory data visualisation and clustering on tabular datanot DVC
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.
Orange
- Orange is licensed under the GNU General Public License version 3, so distributing modified or derived software requires releasing the source under the GPL
- The widgets and canvas are built on Qt, which is itself distributed under GPL 3.0
- Orange add-ons may carry additional licensing requirements set in their own licence files
- Documentation and website content are under Creative Commons Attribution-ShareAlike, which imposes an attribution and share-alike obligation on reuse
- The software is distributed without any warranty of merchantability or fitness for a particular purpose
Pricing, plan by plan
DVC
Free- Open SourceFree
- Data versioning
- Pipeline management
- Experiment tracking
- DVC StudioFree
- Web UI
- Team collaboration
- Visualizations
Orange
Free- Open SourceFree
- Visual programming
- Machine learning
- Data visualization
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 Orange if
- You need visual programming.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want data visualization.
Questions people ask
- Is DVC or Orange better?
- Neither clearly leads. DVC starts at Free and Orange at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, DVC or Orange?
- DVC starts at Free and Orange at Free.
- Does DVC or Orange run on more platforms?
- Both run on Linux, Mac, Windows, so platform support will not decide this one for you.
- 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. Of those, machine learning and data analysis are not what Orange is typically brought in for.
- What can DVC do that Orange cannot?
- DVC covers Data versioning, Pipeline management, Experiment tracking, Remote storage. Orange covers Visual programming, Data visualization, Machine learning, Text mining. Both handle Linux support, Mac support, Windows support.
Related pages
Other head to heads
- DVC vs AWS SageMaker
- DVC vs Google Vertex AI
- DVC vs Azure Machine Learning
- DVC vs DataRobot
- DVC vs Snowflake
- DVC vs TensorFlow
- DVC vs Comet ML
- DVC vs Keras
- DVC vs MLflow
- DVC vs Jupyter
- DVC vs PyTorch
- DVC vs scikit-learn
- DVC vs Apache Spark MLlib
- DVC vs Weights & Biases
- DVC vs Alteryx
- DVC vs Anaconda
- DVC vs Databricks
- DVC vs Dataiku
- Orange vs AWS SageMaker
- Orange vs Google Vertex AI
- Orange vs Azure Machine Learning
- Orange vs DataRobot
- Orange vs Snowflake
- Orange vs TensorFlow
- Orange vs Comet ML
- Orange vs Keras
- Orange vs MLflow
- Orange vs Jupyter
- Orange vs PyTorch
- Orange vs scikit-learn
- Orange vs Apache Spark MLlib
- Orange vs Weights & Biases
- Orange vs Alteryx
- Orange vs Anaconda
- Orange vs Databricks
- Orange vs Dataiku
