Machine Learning & Data Science · head to head
KNIME vs Databricks
KNIME
Machine Learning & Data Science
Open source data analytics and integration platform
- From
- Free
- Rated
- -
Databricks
Machine Learning & Data Science
Unified analytics platform for data engineering and data science
- From
- Free
- Rated
- -
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; Databricks cloud compute is billed separately by the cloud provider on top of Databricks DBU charges
- They diverge on capability: KNIME covers Visual workflows, Databricks covers Delta Lake.
Where they differ
Only the attributes on which KNIME and Databricks actually diverge.
| Attribute | KNIME | Databricks |
|---|---|---|
| Pricing model | freemium | usage-based |
| Platforms | Linux, Mac, Windows | Web, Aws, Azure, Gcp |
| Category | Machine Learning & Data Science | Unknown |
| Founded | 2004 | 2013 |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).
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 Databricks
- Delta Lake
- Apache Spark
- MLflow
- Unity Catalog
- Photon Engine
- Collaborative Notebooks
- Auto-scaling
- AWS
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 Databricks
- Connecting and blending data across many sources for analysisnot Databricks
Databricks
- Running Spark data engineering pipelines on managed clustersnot KNIME
- Building a lakehouse over data in cloud object storagenot KNIME
- Training and serving machine learning models alongside the datanot 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
Databricks
- Cloud compute is billed separately by the cloud provider on top of Databricks DBU charges
- The free trial lasts 14 days
- Discounts require a Committed Use Contract, with larger commitments needed for larger discounts
- Azure Databricks pricing is set by Microsoft rather than by Databricks
- Security and compliance capabilities are sold as separate platform add ons rather than included in the base rate
Pricing, plan by plan
KNIME
Free- Analytics PlatformFree
- Visual workflows
- All nodes
- Community extensions
- ServerFree
- Team collaboration
- Workflow automation
- REST API
Databricks
Free- Community EditionFree
- Limited cluster
- Notebook environment
- Community support
- Standard$0.07/DBU
- Jobs compute
- SQL compute
- Standard support
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 Databricks if
- You need delta lake.
- You want to start without paying.
- You work on Web, Aws, Azure, Gcp.
- You also want apache spark.
Questions people ask
- Is KNIME or Databricks better?
- Neither clearly leads. KNIME starts at Free and Databricks at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, KNIME or Databricks?
- KNIME starts at Free and Databricks at Free.
- Does KNIME or Databricks run on more platforms?
- KNIME runs on Linux, Mac, Windows. Databricks runs on Web, Aws, Azure, Gcp.
- 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 Databricks is typically brought in for.
- What can KNIME do that Databricks cannot?
- KNIME covers Visual workflows, Data preprocessing, Machine learning, Visualization. Databricks covers Delta Lake, Apache Spark, MLflow, Unity Catalog.