Cube VS Databricks AI/BI Genie
As of 30 October 2026, Databricks AI/BI Genie is named by 183 companies and Cube by 198; Cube skews to companies under 200 people (38% vs 23%), Databricks AI/BI Genie to companies over 1,000 (53% vs 31%).
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: Cube'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.
- Cube: 2–200 employees
- 38%
- Databricks AI/BI Genie: 2–200 employees
- 23%
- Cube: 1,000+ employees
- 31%
- 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 | Cube | share | Databricks AI/BI Genie | share | Leans |
|---|---|---|---|---|---|
| Self-employed | 3 | 2% | 2 | 1% | even |
| 2-10 employees | 8 | 4% | 6 | 3% | even |
| 11-50 employees | 24 | 12% | 9 | 5% | Cube |
| 51-200 employees | 44 | 22% | 27 | 15% | Cube |
| 201-500 employees | 40 | 20% | 24 | 13% | Cube |
| 501-1000 employees | 17 | 9% | 18 | 10% | even |
| 1001-5000 employees | 32 | 16% | 39 | 21% | Databricks AI/BI Genie |
| 5001-10000 employees | 8 | 4% | 13 | 7% | Databricks AI/BI Genie |
| 10,001+ employees | 22 | 11% | 45 | 25% | Databricks AI/BI Genie |
| Segment | Cube | share | Databricks AI/BI Genie | share | Leans |
|---|---|---|---|---|---|
| Technology & software | 78 | 39% | 45 | 25% | Cube |
| Business & finance services | 50 | 25% | 52 | 28% | Databricks AI/BI Genie |
| Manufacturing & industry | 19 | 10% | 23 | 13% | Databricks AI/BI Genie |
| Property & construction | 11 | 6% | 11 | 6% | even |
| Media & content | 10 | 5% | 7 | 4% | even |
| Commerce & trade | 6 | 3% | 8 | 4% | even |
| Health care | 6 | 3% | 7 | 4% | even |
| Public, community & associations | 5 | 3% | 5 | 3% | even |
| Transport, logistics & rental | 5 | 3% | 4 | 2% | even |
| Consumer services & leisure | 3 | 2% | – | – | outside top 12 |
| Automotive | 2 | 1% | 8 | 4% | Databricks AI/BI Genie |
| Utilities & infrastructure | 2 | 1% | 6 | 3% | Databricks AI/BI Genie |
| Hospitality & travel | – | – | 4 | 2% | outside top 12 |
| Segment | Cube | share | Databricks AI/BI Genie | share | Leans |
|---|---|---|---|---|---|
| United States | 139 | 70% | 119 | 65% | Cube |
| United Kingdom | 13 | 7% | 12 | 7% | even |
| Germany | 6 | 3% | 7 | 4% | even |
| Canada | 5 | 3% | 7 | 4% | even |
| India | 4 | 2% | – | – | outside top 12 |
| Netherlands | 4 | 2% | 3 | 2% | even |
| France | 3 | 2% | 5 | 3% | even |
| Italy | 3 | 2% | – | – | outside top 12 |
| Brazil | 2 | 1% | 3 | 2% | even |
| Denmark | 2 | 1% | 2 | 1% | even |
| Spain | 2 | 1% | – | – | outside top 12 |
| Japan | 2 | 1% | – | – | outside top 12 |
| Australia | – | – | 6 | 3% | outside top 12 |
| Austria | – | – | 2 | 1% | outside top 12 |
| Switzerland | – | – | 2 | 1% | outside top 12 |
| Finland | – | – | 2 | 1% | outside top 12 |
| Segment | Cube | share | Databricks AI/BI Genie | share | Leans |
|---|---|---|---|---|---|
| Data & AI | 136 | 24% | 391 | 20% | Cube |
| IT operations & business systems | 117 | 21% | 216 | 11% | Cube |
| Engineering (non-software) | 41 | 7% | 18 | 1% | Cube |
| Software engineering | 35 | 6% | 400 | 21% | Databricks AI/BI Genie |
| Finance & accounting | 28 | 5% | 19 | 1% | Cube |
| Construction and civil | 14 | 2% | – | – | outside top 12 |
| Quality, safety & environment | 13 | 2% | – | – | outside top 12 |
| Product, program & project management | 12 | 2% | 101 | 5% | Databricks AI/BI Genie |
| Sales | 9 | 2% | 369 | 19% | Databricks AI/BI Genie |
| Legal, compliance & risk | 5 | 1% | – | – | outside top 12 |
| Logistics warehouse and transport | 4 | 1% | – | – | outside top 12 |
| Arts media and entertainment | 2 | 0% | – | – | outside top 12 |
| Marketing & communications | – | – | 37 | 2% | outside top 12 |
| Customer service & success | – | – | 20 | 1% | outside top 12 |
| Human resources | – | – | 20 | 1% | outside top 12 |
| Business development & strategy | – | – | 17 | 1% | outside top 12 |
| Design & UX | – | – | 11 | 1% | outside top 12 |
The companies behind each column
Companies using Cube →
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 Cube by 198; 0 name both. (Breaknorm, 30 October 2026, https://breaknorm.co/compare/cube-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.
Cube vs Databricks AI/BI Genie: questions
Which is more used, Cube or Databricks AI/BI Genie?
By companies naming it in their own job postings, Cube (198) 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 Cube?
38% of Cube companies have 2 to 200 employees, against 23% for Databricks AI/BI Genie. 31% of Cube 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 Cube 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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