Apache Superset VS Databricks AI/BI Genie
As of 30 October 2026, Databricks AI/BI Genie is named by 183 companies and Apache Superset by 218; Apache Superset skews to companies under 200 people (50% vs 23%), Databricks AI/BI Genie to companies over 1,000 (53% vs 32%).
As of 30 October 2026 · refreshed daily · counts move as websites, DNS and career sites are re-read.
The website-and-DNS footprint is not comparable between a marketing suite and a CRM: Apache Superset's script and mail records show on hundreds of thousands of small sites, Databricks AI/BI Genie rarely leaves a trace outside its own apps. Compare on the job-posting numbers; use the footprint for reach.
- Apache Superset: 2–200 employees
- 50%
- Databricks AI/BI Genie: 2–200 employees
- 23%
- Apache Superset: 1,000+ employees
- 32%
- Databricks AI/BI Genie: 1,000+ employees
- 53%
- Postings per company, 90 days
- 2.0 · 7.3
- Website or DNS footprint
- 0 · 0
Who chooses which
Share of each tool's companies in every segment. "Leans" marks a gap of more than two points.
| Segment | Apache Superset | share | Databricks AI/BI Genie | share | Leans |
|---|---|---|---|---|---|
| Self-employed | 5 | 2% | 2 | 1% | even |
| 2-10 employees | 12 | 6% | 6 | 3% | Apache Superset |
| 11-50 employees | 43 | 20% | 9 | 5% | Apache Superset |
| 51-200 employees | 55 | 25% | 27 | 15% | Apache Superset |
| 201-500 employees | 22 | 10% | 24 | 13% | Databricks AI/BI Genie |
| 501-1000 employees | 11 | 5% | 18 | 10% | Databricks AI/BI Genie |
| 1001-5000 employees | 40 | 18% | 39 | 21% | Databricks AI/BI Genie |
| 5001-10000 employees | 9 | 4% | 13 | 7% | Databricks AI/BI Genie |
| 10,001+ employees | 21 | 10% | 45 | 25% | Databricks AI/BI Genie |
| Segment | Apache Superset | share | Databricks AI/BI Genie | share | Leans |
|---|---|---|---|---|---|
| Technology & software | 100 | 46% | 45 | 25% | Apache Superset |
| Business & finance services | 46 | 21% | 52 | 28% | Databricks AI/BI Genie |
| Media & content | 19 | 9% | 7 | 4% | Apache Superset |
| Manufacturing & industry | 18 | 8% | 23 | 13% | Databricks AI/BI Genie |
| Public, community & associations | 11 | 5% | 5 | 3% | Apache Superset |
| Consumer services & leisure | 4 | 2% | – | – | outside top 12 |
| Transport, logistics & rental | 4 | 2% | 4 | 2% | even |
| Utilities & infrastructure | 4 | 2% | 6 | 3% | even |
| Commerce & trade | 3 | 1% | 8 | 4% | Databricks AI/BI Genie |
| Health care | 3 | 1% | 7 | 4% | Databricks AI/BI Genie |
| Automotive | 2 | 1% | 8 | 4% | Databricks AI/BI Genie |
| Hospitality & travel | 2 | 1% | 4 | 2% | even |
| Property & construction | – | – | 11 | 6% | outside top 12 |
| Segment | Apache Superset | share | Databricks AI/BI Genie | share | Leans |
|---|---|---|---|---|---|
| United States | 121 | 56% | 119 | 65% | Databricks AI/BI Genie |
| United Kingdom | 19 | 9% | 12 | 7% | Apache Superset |
| France | 10 | 5% | 5 | 3% | even |
| India | 10 | 5% | – | – | outside top 12 |
| Germany | 7 | 3% | 7 | 4% | even |
| Belgium | 4 | 2% | – | – | outside top 12 |
| Brazil | 4 | 2% | 3 | 2% | even |
| Switzerland | 4 | 2% | 2 | 1% | even |
| Singapore | 4 | 2% | – | – | outside top 12 |
| Australia | 3 | 1% | 6 | 3% | even |
| Canada | 3 | 1% | 7 | 4% | Databricks AI/BI Genie |
| China | 2 | 1% | – | – | outside top 12 |
| Netherlands | – | – | 3 | 2% | outside top 12 |
| Austria | – | – | 2 | 1% | outside top 12 |
| Denmark | – | – | 2 | 1% | outside top 12 |
| Finland | – | – | 2 | 1% | outside top 12 |
| Segment | Apache Superset | share | Databricks AI/BI Genie | share | Leans |
|---|---|---|---|---|---|
| Data & AI | 291 | 49% | 391 | 20% | Apache Superset |
| Software engineering | 73 | 12% | 400 | 21% | Databricks AI/BI Genie |
| Product, program & project management | 37 | 6% | 101 | 5% | even |
| Marketing & communications | 31 | 5% | 37 | 2% | Apache Superset |
| IT operations & business systems | 20 | 3% | 216 | 11% | Databricks AI/BI Genie |
| Finance & accounting | 15 | 3% | 19 | 1% | even |
| Legal, compliance & risk | 13 | 2% | – | – | outside top 12 |
| Sales | 11 | 2% | 369 | 19% | Databricks AI/BI Genie |
| Engineering (non-software) | 7 | 1% | 18 | 1% | even |
| Business development & strategy | 6 | 1% | 17 | 1% | even |
| Customer service & success | 2 | 0% | 20 | 1% | even |
| General management & consulting | 2 | 0% | – | – | outside top 12 |
| Human resources | – | – | 20 | 1% | outside top 12 |
| Design & UX | – | – | 11 | 1% | outside top 12 |
The companies behind each column
Companies using Apache Superset →
Companies using Databricks AI/BI Genie →
BI & reporting ranked →
Quote the sentence with the date and the link. The numbers change daily; the link always shows the current ones.
Databricks AI/BI Genie is named by 183 companies in job postings and Apache Superset by 218; 0 name both. (Breaknorm, 30 October 2026, https://breaknorm.co/compare/apache-superset-vs-databricks-genie)
Read from the source, not self-reported
Every number on this page can be traced to a page we crawled or a posting we read. Full methodology →
- Job postingsRead hourly from career sites. A tool counts when the employer's own text names it as the team's system; both tools can count for one company.
- Website and DNSScripts and embeds on the company's pages, plus SPF, DKIM, MX and CNAME records of its domain that point at the vendor.
- SegmentsCountry, size and industry from the company profile built from its website.
- Not a reviewNo ratings, prices or feature claims. For those, read the vendors.
Apache Superset vs Databricks AI/BI Genie: questions
Which is more used, Apache Superset or Databricks AI/BI Genie?
By companies naming it in their own job postings, Apache Superset (218) over Databricks AI/BI Genie (183). By website-and-DNS footprint, Databricks AI/BI Genie (0 vs 0), because its scripts and mail records sit on many small company sites.
Who chooses Apache Superset?
50% of Apache Superset companies have 2 to 200 employees, against 23% for Databricks AI/BI Genie. 32% of Apache Superset companies have over 1,000 employees, against 53% for Databricks AI/BI Genie.
Do companies run both?
0 companies name both in their postings, usually Apache Superset in marketing and Databricks AI/BI Genie in sales, or during a migration.
Where do these numbers come from?
From the employer's own text in job postings read hourly from career sites, and from scripts found on company websites in our crawl. No vendor data, no surveys.
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