Software · head to head
KNIME vs DVC
The short version
- Each has a real cost: KNIME the free Analytics Platform runs locally only, so anything shared or scheduled requires a paid Hub; 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.
- They diverge on capability: KNIME covers Visual workflows, DVC covers Data versioning.
Where they differ
Only the attributes on which KNIME and DVC actually diverge.
Identical on both: starting price (Free), free tier (Yes), platforms (Linux, Mac, Windows), 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 KNIME
- Visual workflows
- Data preprocessing
- Machine learning
- Visualization
- Reporting
- Python
- R
- Spark
Only in DVC
- Data versioning
- Pipeline management
- Experiment tracking
- Remote storage
- Git integration
- Git
- S3
- Azure Blob
Both cover
- Linux support
- Mac support
- Windows support
What people use each for
The jobs each tool is most often brought in to do.
KNIME
- Building data pipelines and analytics workflows visually rather than in codenot DVC
- Connecting and blending data across many sources for analysisnot DVC
DVC
- Machine learningnot KNIME
- Data analysisnot KNIME
- Model trainingnot KNIME
- Predictive analyticsnot KNIME
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
KNIME
- The free Analytics Platform runs locally only, so anything shared or scheduled requires a paid Hub
- The free AI assistant is limited to 20 interactions a month
- Paid workflow runtime is metered in credits, with 120 included on Pro and overage at $0.025 per vCore minute
- The Team plan at $99 a month includes 3 members, with additional seats at $49 a month each
- Business Hub pricing is on request, and its tiers are capped at 4, 8 and 16 vCores with 5, 5 and 20 users
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.
Pricing, plan by plan
KNIME
Free- Analytics PlatformFree
- Visual workflows
- All nodes
- Community extensions
- ServerFree
- Team collaboration
- Workflow automation
- REST API
DVC
Free- Open SourceFree
- Data versioning
- Pipeline management
- Experiment tracking
- DVC StudioFree
- Web UI
- Team collaboration
- Visualizations
Which should you pick?
Choose KNIME if
- You need visual workflows.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want data preprocessing.
Choose DVC if
- You need data versioning.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want pipeline management.
Questions people ask
- Is KNIME or DVC better?
- Neither clearly leads. KNIME starts at Free and DVC at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, KNIME or DVC?
- KNIME starts at Free and DVC at Free.
- Does KNIME or DVC run on more platforms?
- Both run on Linux, Mac, Windows, so platform support will not decide this one for you.
- Can I use KNIME for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is KNIME best used for?
- KNIME is most often used for building data pipelines and analytics workflows visually rather than in code, connecting and blending data across many sources for analysis. Of those, building data pipelines and analytics workflows visually rather than in code and connecting and blending data across many sources for analysis are not what DVC is typically brought in for.
- What can KNIME do that DVC cannot?
- KNIME covers Visual workflows, Data preprocessing, Machine learning, Visualization. DVC covers Data versioning, Pipeline management, Experiment tracking, Remote storage. Both handle Linux support, Mac support, Windows support.