Dataiku VS Jupyter
As of 30 October 2026, Jupyter is named by 528 companies and Dataiku by 149; Dataiku skews to companies under 200 people (29% vs 44%), Jupyter to companies over 1,000 (31% vs 50%).
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: Dataiku's script and mail records show on hundreds of thousands of small sites, Jupyter rarely leaves a trace outside its own apps. Compare on the job-posting numbers; use the footprint for reach.
- Dataiku: 2–200 employees
- 29%
- Jupyter: 2–200 employees
- 44%
- Dataiku: 1,000+ employees
- 50%
- Jupyter: 1,000+ employees
- 31%
- Postings per company, 90 days
- 3.7 · 2.0
- 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 | Dataiku | share | Jupyter | share | Leans |
|---|---|---|---|---|---|
| Self-employed | 1 | 1% | 13 | 2% | even |
| 2-10 employees | 7 | 5% | 35 | 7% | even |
| 11-50 employees | 14 | 9% | 85 | 16% | Jupyter |
| 51-200 employees | 22 | 15% | 110 | 21% | Jupyter |
| 201-500 employees | 17 | 11% | 65 | 12% | even |
| 501-1000 employees | 13 | 9% | 54 | 10% | even |
| 1001-5000 employees | 24 | 16% | 70 | 13% | Dataiku |
| 5001-10000 employees | 11 | 7% | 20 | 4% | Dataiku |
| 10,001+ employees | 40 | 27% | 76 | 14% | Dataiku |
| Segment | Dataiku | share | Jupyter | share | Leans |
|---|---|---|---|---|---|
| Technology & software | 51 | 34% | 253 | 48% | Jupyter |
| Business & finance services | 49 | 33% | 105 | 20% | Dataiku |
| Manufacturing & industry | 23 | 15% | 46 | 9% | Dataiku |
| Automotive | 6 | 4% | 6 | 1% | Dataiku |
| Health care | 5 | 3% | – | – | outside top 12 |
| Public, community & associations | 3 | 2% | 27 | 5% | Jupyter |
| Utilities & infrastructure | 3 | 2% | 17 | 3% | even |
| Commerce & trade | 2 | 1% | 9 | 2% | even |
| Consumer services & leisure | 2 | 1% | 29 | 5% | Jupyter |
| Transport, logistics & rental | 2 | 1% | 8 | 2% | even |
| Hospitality & travel | 1 | 1% | 5 | 1% | even |
| Media & content | 1 | 1% | 15 | 3% | Jupyter |
| Agriculture & forestry | – | – | 3 | 1% | outside top 12 |
| Segment | Dataiku | share | Jupyter | share | Leans |
|---|---|---|---|---|---|
| United States | 62 | 42% | 339 | 64% | Jupyter |
| France | 51 | 34% | 18 | 3% | Dataiku |
| United Kingdom | 10 | 7% | 44 | 8% | even |
| Switzerland | 4 | 3% | – | – | outside top 12 |
| Canada | 3 | 2% | 12 | 2% | even |
| Australia | 2 | 1% | – | – | outside top 12 |
| Belgium | 2 | 1% | 4 | 1% | even |
| Germany | 2 | 1% | 25 | 5% | Jupyter |
| Denmark | 2 | 1% | – | – | outside top 12 |
| Luxembourg | 2 | 1% | – | – | outside top 12 |
| Singapore | 2 | 1% | 9 | 2% | even |
| United Arab Emirates | 1 | 1% | – | – | outside top 12 |
| India | – | – | 10 | 2% | outside top 12 |
| Poland | – | – | 6 | 1% | outside top 12 |
| Spain | – | – | 5 | 1% | outside top 12 |
| Netherlands | – | – | 5 | 1% | outside top 12 |
| Brazil | – | – | 4 | 1% | outside top 12 |
| Segment | Dataiku | share | Jupyter | share | Leans |
|---|---|---|---|---|---|
| Data & AI | 451 | 57% | 738 | 49% | Dataiku |
| IT operations & business systems | 46 | 6% | 70 | 5% | even |
| Finance & accounting | 40 | 5% | 26 | 2% | Dataiku |
| Software engineering | 37 | 5% | 212 | 14% | Jupyter |
| Product, program & project management | 33 | 4% | 21 | 1% | Dataiku |
| General management & consulting | 17 | 2% | 10 | 1% | even |
| Sales | 15 | 2% | 22 | 1% | even |
| Marketing & communications | 14 | 2% | – | – | outside top 12 |
| Legal, compliance & risk | 7 | 1% | 19 | 1% | even |
| Customer service & success | 5 | 1% | 14 | 1% | even |
| Arts media and entertainment | 2 | 0% | – | – | outside top 12 |
| Procurement and purchasing | 2 | 0% | – | – | outside top 12 |
| Engineering (non-software) | – | – | 67 | 4% | outside top 12 |
| Research and science | – | – | 29 | 2% | outside top 12 |
| Education & training | – | – | 21 | 1% | outside top 12 |
The companies behind each column
Companies using Dataiku →
Companies using Jupyter →
data science platforms notebooks ranked →
Quote the sentence with the date and the link. The numbers change daily; the link always shows the current ones.
Jupyter is named by 528 companies in job postings and Dataiku by 149; 12 name both. (Breaknorm, 30 October 2026, https://breaknorm.co/compare/dataiku-vs-jupyter)
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.
Dataiku vs Jupyter: questions
Which is more used, Dataiku or Jupyter?
By companies naming it in their own job postings, Jupyter (528) over Dataiku (149). By website-and-DNS footprint, Jupyter (0 vs 0), because its scripts and mail records sit on many small company sites.
Who chooses Dataiku?
29% of Dataiku companies have 2 to 200 employees, against 44% for Jupyter. 50% of Dataiku companies have over 1,000 employees, against 31% for Jupyter.
Do companies run both?
12 companies name both in their postings, usually Dataiku in marketing and Jupyter 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.
Get either list your way
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with the person who owns it
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