Machine Learning & Data Science · head to head
Databricks vs JMP

Databricks
Machine Learning & Data Science
Unified analytics platform for data engineering and data science
- From
- Free
- Rated
- -

JMP
Machine Learning & Data Science
Statistical discovery software from SAS
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Databricks cloud compute is billed separately by the cloud provider on top of Databricks DBU charges; JMP the Internet Archive's capture of JMP's homepage on 13 January 2020 named five distinct editions, JMP, JMP Live, JMP Pro, JMP Clinical, and JMP Genomics, each targeting a different analysis use case, with no price figure published for any.
- They diverge on capability: Databricks covers Delta Lake, JMP covers Interactive statistics.
Where they differ
Only the attributes on which Databricks and JMP actually diverge.
| Attribute | Databricks | JMP |
|---|---|---|
| Pricing model | usage-based | subscription |
| Platforms | Web, Aws, Azure, Gcp | Mac, Windows |
| Founded | 2013 | 1976 |
Identical on both: starting price (Free), free tier (Yes), 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 Databricks
- Delta Lake
- Apache Spark
- MLflow
- Unity Catalog
- Photon Engine
- Collaborative Notebooks
- Auto-scaling
- AWS
Only in JMP
- Interactive statistics
- Dynamic visualization
- Design of experiments
- Predictive modeling
- Quality control
- SAS
- Python
- R
What people use each for
The jobs each tool is most often brought in to do.
Databricks
- Running Spark data engineering pipelines on managed clustersnot JMP
- Building a lakehouse over data in cloud object storagenot JMP
- Training and serving machine learning models alongside the datanot JMP
JMP
- Machine learningnot Databricks
- Data analysisnot Databricks
- Model trainingnot Databricks
- Predictive analyticsnot Databricks
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
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
JMP
- The Internet Archive's capture of JMP's homepage on 13 January 2020 named five distinct editions, JMP, JMP Live, JMP Pro, JMP Clinical, and JMP Genomics, each targeting a different analysis use case, with no price figure published for any.
Pricing, plan by plan
Databricks
Free- Community EditionFree
- Limited cluster
- Notebook environment
- Community support
- Standard$0.07/DBU
- Jobs compute
- SQL compute
- Standard support
JMP
Free- TrialFree
- 30-day trial
- Full features
- JMP$1785/year
- Core JMP
- Standard features
Which should you pick?
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.
Choose JMP if
- You need interactive statistics.
- You want to start without paying.
- You work on Mac, Windows.
- You also want dynamic visualization.
Questions people ask
- Is Databricks or JMP better?
- Neither clearly leads. Databricks starts at Free and JMP at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Databricks or JMP?
- Databricks starts at Free and JMP at Free.
- Does Databricks or JMP run on more platforms?
- Databricks runs on Web, Aws, Azure, Gcp. JMP runs on Mac, Windows.
- Can I use Databricks for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Databricks best used for?
- Databricks is most often used for running spark data engineering pipelines on managed clusters, building a lakehouse over data in cloud object storage, training and serving machine learning models alongside the data. Of those, running spark data engineering pipelines on managed clusters and building a lakehouse over data in cloud object storage are not what JMP is typically brought in for.
- What can Databricks do that JMP cannot?
- Databricks covers Delta Lake, Apache Spark, MLflow, Unity Catalog. JMP covers Interactive statistics, Dynamic visualization, Design of experiments, Predictive modeling.
Related pages
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- JMP vs Google Vertex AI
- JMP vs Azure Machine Learning
- JMP vs DataRobot
- JMP vs Snowflake
- JMP vs TensorFlow
- JMP vs Comet ML
- JMP vs Keras
- JMP vs MLflow
- JMP vs Jupyter
- JMP vs PyTorch
- JMP vs scikit-learn
- JMP vs Apache Spark MLlib
- JMP vs Weights & Biases
- JMP vs Alteryx
- JMP vs Anaconda
- JMP vs Dataiku
- JMP vs DVC
