Machine Learning · head to head
Databricks vs Mode

Databricks
Machine Learning
Unified analytics platform for data engineering and data science
- 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; Mode free tier limited to 4GB RAM and 1 CPU for SQL notebooks, insufficient for large datasets
- They diverge on capability: Databricks covers Delta Lake, Mode covers SQL Editor.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Databricks and Mode actually diverge.
| Attribute | Databricks | Mode |
|---|---|---|
| Pricing model | usage-based | subscription |
| Platforms | Web, Aws, Azure, Gcp | Web |
| Category | Machine Learning | Business Intelligence |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), founded (2013).
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 Mode
- SQL Editor
- Python/R Notebooks
- Interactive Reports
- Version Control
- Scheduling
- Snowflake
- Redshift
- BigQuery
Both cover
- Web support
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 Mode
- Building a lakehouse over data in cloud object storagenot Mode
- Training and serving machine learning models alongside the datanot Mode
Mode
- Self-service analyticsnot Databricks
- Data explorationnot Databricks
- Ad-hoc reportingnot Databricks
- Collaborative analysisnot Databricks
- Embedded 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
Mode
- Free tier limited to 4GB RAM and 1 CPU for SQL notebooks, insufficient for large datasets
- Requires SQL knowledge for most analysis tasks, creating dependency on technical resources
- Paid plan pricing not publicly listed; requires sales consultation
- Recently acquired by ThoughtSpot in 2026, creating product direction uncertainty
- Limited customization options for visual aspects and embedded analytics
Pricing, plan by plan
Databricks
Free- Community EditionFree
- Limited cluster
- Notebook environment
- Community support
- Standard$0.07/DBU
- Jobs compute
- SQL compute
- Standard support
Mode
Free- FreeFree
- SQL Editor
- Python/R Notebooks
- Basic Charts
- Business$65/month
- Advanced Visualizations
- Collaboration
- Integrations
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 Mode if
- You need sql editor.
- You want to start without paying.
- You also want python/r notebooks.
Questions people ask
- Is Databricks or Mode better?
- Neither clearly leads. Databricks starts at Free and Mode at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Databricks or Mode?
- Databricks starts at Free and Mode at Free.
- Does Databricks or Mode run on more platforms?
- Databricks runs on Web, Aws, Azure, Gcp. Mode runs on Web.
- 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 Mode is typically brought in for.
- What can Databricks do that Mode cannot?
- Databricks covers Delta Lake, Apache Spark, MLflow, Unity Catalog. Mode covers SQL Editor, Python/R Notebooks, Interactive Reports, Version Control. Both handle Web support.
Answered from the vendors’ own pages
Databricks: How is Databricks priced?
Databricks bills pay as you go with no up front cost, charging per second for the products used. Consumption is measured in Databricks Units, a normalised unit of processing power on the platform.
SourceMode: What languages does Mode support for analysis?
Mode notebooks support SQL, Python (3.11 with pandas, NumPy, scikit-learn, matplotlib), and R (4.2.0 with ggplot2, dplyr, tidyr). Both Python and R allow additional library installation at runtime.
SourceDatabricks: Does Databricks publish a per DBU price?
Not on its main pricing page. Rates vary by product and instance type, and Databricks directs buyers to individual product pricing pages and a calculator rather than listing a single figure.
SourceMode: Can I integrate Mode notebook results into reports?
Yes. Mode allows adding notebook cell results directly to reports, with synchronized scheduling so reports re-run to keep data current.
SourceDatabricks: Does the Databricks price include cloud costs?
No. Databricks states that if you configure it to work with your own cloud account, your cloud provider still charges you separately for the underlying resources.
SourceMode: Does Mode support collaborative analysis?
Yes. Mode notebooks provide moveable code blocks and markdown cells enabling exploratory analysis and team collaboration on data queries and visualizations.
SourceDatabricks: Can I get a discount on Databricks?
Databricks offers Committed Use Contracts, where larger usage commitments earn greater benefits, including options to use commitments flexibly across multiple clouds.
SourceRelated pages
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- Databricks vs Snowflake
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- Databricks vs Deepnote
- Databricks vs Yellowfin
- Databricks vs TIBCO Spotfire
- Databricks vs Hex
- Databricks vs GoodData
- Databricks vs Grow
- Databricks vs Qlik Sense
- Databricks vs Databox
- Databricks vs Cube
- Databricks vs Jedox
- Databricks vs Logi Analytics
- Databricks vs Luzmo
- Databricks vs NetBase Quid
- Databricks vs Phocas
- Databricks vs Preset
- Mode vs AWS SageMaker
- Mode vs Google Vertex AI
- Mode vs Azure Machine Learning
- Mode vs DataRobot
- Mode vs TensorFlow
- Mode vs SAS
- Mode vs Snowflake
- Mode vs Apache Spark MLlib
- Mode vs Alteryx
- Mode vs IBM SPSS
- Mode vs Palantir Foundry
- Mode vs BentoML
- Mode vs ClearML
- Mode vs Cohere
- Mode vs Dask
- Mode vs Fal AI
- Mode vs BigQuery ML
- Mode vs Periscope Data
- Mode vs Domo
- Mode vs Fabi
- Mode vs Deepnote
- Mode vs Yellowfin
- Mode vs TIBCO Spotfire
- Mode vs Hex
- Mode vs GoodData
- Mode vs Grow
- Mode vs Qlik Sense
- Mode vs Databox
- Mode vs Cube
- Mode vs Jedox
- Mode vs Logi Analytics
- Mode vs Luzmo
- Mode vs NetBase Quid
- Mode vs Phocas
- Mode vs Preset

