DataHub VS Monte Carlo
As of 30 October 2026, Monte Carlo is named by 113 companies and DataHub by 127; DataHub skews to companies under 200 people (30% vs 30%), Monte Carlo to companies over 1,000 (39% vs 40%).
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: DataHub's script and mail records show on hundreds of thousands of small sites, Monte Carlo rarely leaves a trace outside its own apps. Compare on the job-posting numbers; use the footprint for reach.
- DataHub: 2–200 employees
- 30%
- Monte Carlo: 2–200 employees
- 30%
- DataHub: 1,000+ employees
- 40%
- Monte Carlo: 1,000+ employees
- 39%
- Postings per company, 90 days
- 2.8 · 2.7
- 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 | DataHub | share | Monte Carlo | share | Leans |
|---|---|---|---|---|---|
| Self-employed | 3 | 2% | – | – | outside top 12 |
| 2-10 employees | 3 | 2% | 8 | 7% | Monte Carlo |
| 11-50 employees | 15 | 12% | 9 | 8% | DataHub |
| 51-200 employees | 20 | 16% | 17 | 15% | even |
| 201-500 employees | 21 | 17% | 17 | 15% | even |
| 501-1000 employees | 14 | 11% | 18 | 16% | Monte Carlo |
| 1001-5000 employees | 31 | 24% | 21 | 19% | DataHub |
| 5001-10000 employees | 5 | 4% | 3 | 3% | even |
| 10,001+ employees | 15 | 12% | 20 | 18% | Monte Carlo |
| Segment | DataHub | share | Monte Carlo | share | Leans |
|---|---|---|---|---|---|
| Technology & software | 55 | 43% | 34 | 30% | DataHub |
| Business & finance services | 34 | 27% | 30 | 27% | even |
| Manufacturing & industry | 13 | 10% | 18 | 16% | Monte Carlo |
| Utilities & infrastructure | 6 | 5% | 2 | 2% | DataHub |
| Consumer services & leisure | 5 | 4% | 2 | 2% | DataHub |
| Media & content | 5 | 4% | 5 | 4% | even |
| Commerce & trade | 4 | 3% | 9 | 8% | Monte Carlo |
| Transport, logistics & rental | 2 | 2% | 1 | 1% | even |
| Automotive | 1 | 1% | – | – | outside top 12 |
| Public, community & associations | 1 | 1% | 5 | 4% | Monte Carlo |
| Hospitality & travel | 1 | 1% | 1 | 1% | even |
| Health care | – | – | 5 | 4% | outside top 12 |
| Property & construction | – | – | 1 | 1% | outside top 12 |
| Segment | DataHub | share | Monte Carlo | share | Leans |
|---|---|---|---|---|---|
| United States | 72 | 57% | 87 | 77% | Monte Carlo |
| United Kingdom | 12 | 9% | 6 | 5% | DataHub |
| France | 8 | 6% | 4 | 4% | DataHub |
| Germany | 6 | 5% | 2 | 2% | DataHub |
| Brazil | 3 | 2% | – | – | outside top 12 |
| Netherlands | 3 | 2% | 1 | 1% | even |
| Belgium | 2 | 2% | 2 | 2% | even |
| Canada | 2 | 2% | 1 | 1% | even |
| Spain | 2 | 2% | – | – | outside top 12 |
| India | 2 | 2% | – | – | outside top 12 |
| Poland | 2 | 2% | – | – | outside top 12 |
| Sweden | 2 | 2% | – | – | outside top 12 |
| Australia | – | – | 3 | 3% | outside top 12 |
| Austria | – | – | 2 | 2% | outside top 12 |
| MK | – | – | 1 | 1% | outside top 12 |
| Mexico | – | – | 1 | 1% | outside top 12 |
| Norway | – | – | 1 | 1% | outside top 12 |
| Segment | DataHub | share | Monte Carlo | share | Leans |
|---|---|---|---|---|---|
| Data & AI | 226 | 49% | 252 | 70% | Monte Carlo |
| Software engineering | 73 | 16% | 8 | 2% | DataHub |
| Healthcare clinical | 42 | 9% | – | – | outside top 12 |
| IT operations & business systems | 21 | 5% | 7 | 2% | DataHub |
| Product, program & project management | 16 | 3% | 13 | 4% | even |
| General management & consulting | 6 | 1% | 2 | 1% | even |
| Finance & accounting | 5 | 1% | 5 | 1% | even |
| Engineering (non-software) | 3 | 1% | 31 | 9% | Monte Carlo |
| Legal, compliance & risk | 2 | 0% | 2 | 1% | even |
| Unclassified | 2 | 0% | – | – | outside top 12 |
| Business development & strategy | 1 | 0% | – | – | outside top 12 |
| Construction and civil | 1 | 0% | 3 | 1% | even |
| Research and science | – | – | 4 | 1% | outside top 12 |
| Quality, safety & environment | – | – | 2 | 1% | outside top 12 |
The companies behind each column
Companies using DataHub →
Companies using Monte Carlo →
data governance quality mdm ranked →
Quote the sentence with the date and the link. The numbers change daily; the link always shows the current ones.
Monte Carlo is named by 113 companies in job postings and DataHub by 127; 12 name both. (Breaknorm, 30 October 2026, https://breaknorm.co/compare/datahub-vs-monte-carlo)
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.
DataHub vs Monte Carlo: questions
Which is more used, DataHub or Monte Carlo?
By companies naming it in their own job postings, DataHub (127) over Monte Carlo (113). By website-and-DNS footprint, Monte Carlo (0 vs 0), because its scripts and mail records sit on many small company sites.
Who chooses DataHub?
30% of DataHub companies have 2 to 200 employees, against 30% for Monte Carlo. 40% of DataHub companies have over 1,000 employees, against 39% for Monte Carlo.
Do companies run both?
12 companies name both in their postings, usually DataHub in marketing and Monte Carlo 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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