Spreadsheet & Data · head to head
Apache Superset vs Databricks

Apache Superset
Spreadsheet & Data
Modern data exploration and visualization 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: Apache Superset distributed under Apache License 2.0 with no official vendor-hosted SaaS; deploying it requires self-managed infrastructure since the Apache Software Foundation does not sell a managed offering.; Databricks cloud compute is billed separately by the cloud provider on top of Databricks DBU charges
- They diverge on capability: Apache Superset covers 40+ Visualizations, Databricks covers Delta Lake.
Where they differ
Only the attributes on which Apache Superset and Databricks actually diverge.
| Attribute | Apache Superset | Databricks |
|---|---|---|
| Pricing model | open-source | usage-based |
| Platforms | Web, Self-hosted, Docker | Web, Aws, Azure, Gcp |
| Category | Spreadsheet & Data | Machine Learning & Data Science |
| Founded | 1999 | 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 Apache Superset
- 40+ Visualizations
- SQL IDE
- Semantic Layer
- Caching
- Security
- PostgreSQL
- MySQL
- Presto
Only in Databricks
- Delta Lake
- Apache Spark
- MLflow
- Unity Catalog
- Photon Engine
- Collaborative Notebooks
- Auto-scaling
- AWS
Both cover
- Web support
What people use each for
The jobs each tool is most often brought in to do.
Apache Superset
- Self-service analyticsnot Databricks
- Data explorationnot Databricks
- Ad-hoc reportingnot Databricks
- Collaborative analysisnot Databricks
- Embedded analyticsnot Databricks
Databricks
- Running Spark data engineering pipelines on managed clustersnot Apache Superset
- Building a lakehouse over data in cloud object storagenot Apache Superset
- Training and serving machine learning models alongside the datanot Apache Superset
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Apache Superset
- Distributed under Apache License 2.0 with no official vendor-hosted SaaS; deploying it requires self-managed infrastructure since the Apache Software Foundation does not sell a managed offering.
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
Apache Superset
Free- Open SourceFree
- Full Features
- Self-hosted
- Community Support
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 Apache Superset if
- You need 40+ visualizations.
- You want to start without paying.
- You work on Web, Self-hosted, Docker.
- You also want sql ide.
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 Apache Superset or Databricks better?
- Neither clearly leads. Apache Superset 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, Apache Superset or Databricks?
- Apache Superset starts at Free and Databricks at Free.
- Does Apache Superset or Databricks run on more platforms?
- Apache Superset runs on Web, Self-hosted, Docker. Databricks runs on Web, Aws, Azure, Gcp.
- Can I use Apache Superset for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Apache Superset best used for?
- Apache Superset is most often used for self-service analytics, data exploration, ad-hoc reporting, collaborative analysis. Of those, self-service analytics and data exploration are not what Databricks is typically brought in for.
- What can Apache Superset do that Databricks cannot?
- Apache Superset covers 40+ Visualizations, SQL IDE, Semantic Layer, Caching. Databricks covers Delta Lake, Apache Spark, MLflow, Unity Catalog. Both handle Web support.
Related pages
More on Apache Superset
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- Databricks vs AWS SageMaker
- Databricks vs Google Vertex AI
- Databricks vs Azure Machine Learning
- Databricks vs DataRobot
- Databricks vs Snowflake
- Databricks vs TensorFlow
- Databricks vs Comet ML
- Databricks vs Keras
- Databricks vs MLflow
- Databricks vs Jupyter
- Databricks vs PyTorch
- Databricks vs scikit-learn
- Databricks vs Apache Spark MLlib
- Databricks vs Weights & Biases
- Databricks vs Alteryx
- Databricks vs Anaconda
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