Apache SupersetOpen source business intelligence from the Apache Software Foundation
vs
DatabricksUnified data, analytics and AI platform on an open lakehouse
Comparison · Business Intelligence · weekly run Nov 2
Apache Superset vs Databricks
Which one do AI engines recommend, and how do they differ on price, fit and features?
The short answer
Apache Superset is the stronger AI pick in Business Intelligence: it has a visibility score of 4.3 versus 4.3 for Databricks.
Choose Apache Superset if…
- modern open-source data exploration and visualization platform
- handles large datasets well
- strong SQL tooling
- free and powerful
Choose Databricks if…
- AI answers describe it more positively (35% vs 25% positive)
- You need ISO 27001 or ISO 27017 or ISO 27018 or ISO 27701 or SOC 1 or SOC 2 Type II or SOC 3 coverage
- Lakehouse architecture combining data warehousing with data lake flexibility
- Strong for machine learning, AI, and data engineering workloads
AI visibility side by side
Latest weekly run · Nov 2
| Metric | Apache Superset | Databricks |
|---|---|---|
| Visibility score | 4.3% | 4.3% |
| Change vs last week | New | New |
| Rank in Business Intelligence | #19 | #18 |
| Share of voice | 1.6% | 1.6% |
| Mentions this run | 8 | 8 |
| Positive in AI answers | 25% | 35% |
The stronger value in each row is marked with a ✓.
Visibility score trend
Weekly runs over the last 60 days
Apache Superset 0pp · Databricks 0pp over 0 weekly runs.
Engine by engine
Apache Superset leads on 1 of 3 engines
ChatGPT
AI Mode
Perplexity
Apache SupersetDatabricks
Head to head in AI answers
0 engine answers name both brands
0Apache Superset ranked higher
0Databricks ranked higher
Features, pricing & fit
| Dimension | Apache Superset | Databricks |
|---|---|---|
| Deployment | — | Available across all major cloud providers |
| Compliance | — | ISO 27001, ISO 27017, ISO 27018, ISO 27701, SOC 1, SOC 2 Type II, SOC 3 |
| Support | — | Technical support on request, Technical documentation |
| Founded | — | 2013 |
| Headquarters | Wilmington, Delaware, United States | San Francisco, CA |
| Employees | 5,000+ | 5,000+ |
| Funding | — | Round at $60B valuation, including secondary sale |
| Best for | — | Data engineering, data science, analytics and AI teams at startups and global enterprises |
Pros and cons
Themes from the AI answers that mention each brand
Apache Superset
- modern open-source data exploration and visualization platform
- handles large datasets well
- strong SQL tooling
- free and powerful
- lower licensing costs
- best suited to teams with technical staff for deployment and SQL
Databricks
- Lakehouse architecture combining data warehousing with data lake flexibility
- Strong for machine learning, AI, and data engineering workloads
- Top customer satisfaction ratings alongside Snowflake
- Free trial and free Edition for learning
- Discounts for annual prepaid commitments
- Complex consumption-based pricing with no single fixed price
- Best only when ML, Spark, or Python skills are central to the team
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
Cite as: SlateIndex, “Apache Superset vs Databricks”, https://slateindex.ai/compare/apache-superset-vs-databricks, data of Nov 2, 2026. Licence: CC BY 4.0.