Apache Storm VS Google Cloud Dataflow
As of 30 October 2026, Google Cloud Dataflow is named by 362 companies and Apache Storm by 125; Apache Storm skews to companies under 200 people (40% vs 38%), Google Cloud Dataflow to companies over 1,000 (38% vs 37%).
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 Storm's script and mail records show on hundreds of thousands of small sites, Google Cloud Dataflow rarely leaves a trace outside its own apps. Compare on the job-posting numbers; use the footprint for reach.
- Apache Storm: 2–200 employees
- 40%
- Google Cloud Dataflow: 2–200 employees
- 38%
- Apache Storm: 1,000+ employees
- 37%
- Google Cloud Dataflow: 1,000+ employees
- 38%
- Postings per company, 90 days
- 2.0 · 3.6
- 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 Storm | share | Google Cloud Dataflow | share | Leans |
|---|---|---|---|---|---|
| Self-employed | 3 | 2% | 3 | 1% | even |
| 2-10 employees | 6 | 5% | 20 | 6% | even |
| 11-50 employees | 22 | 18% | 44 | 12% | Apache Storm |
| 51-200 employees | 22 | 18% | 72 | 20% | Google Cloud Dataflow |
| 201-500 employees | 19 | 15% | 55 | 15% | even |
| 501-1000 employees | 7 | 6% | 30 | 8% | Google Cloud Dataflow |
| 1001-5000 employees | 25 | 20% | 57 | 16% | Apache Storm |
| 5001-10000 employees | 5 | 4% | 19 | 5% | even |
| 10,001+ employees | 16 | 13% | 62 | 17% | Google Cloud Dataflow |
| Segment | Apache Storm | share | Google Cloud Dataflow | share | Leans |
|---|---|---|---|---|---|
| Technology & software | 59 | 47% | 186 | 51% | Google Cloud Dataflow |
| Business & finance services | 37 | 30% | 76 | 21% | Apache Storm |
| Property & construction | 11 | 9% | 4 | 1% | Apache Storm |
| Public, community & associations | 5 | 4% | 6 | 2% | Apache Storm |
| Manufacturing & industry | 5 | 4% | 21 | 6% | even |
| Commerce & trade | 3 | 2% | 21 | 6% | Google Cloud Dataflow |
| Consumer services & leisure | 3 | 2% | 11 | 3% | even |
| Media & content | 1 | 1% | 11 | 3% | Google Cloud Dataflow |
| Utilities & infrastructure | 1 | 1% | 15 | 4% | Google Cloud Dataflow |
| Health care | – | – | 5 | 1% | outside top 12 |
| Transport, logistics & rental | – | – | 3 | 1% | outside top 12 |
| Automotive | – | – | 2 | 1% | outside top 12 |
| Segment | Apache Storm | share | Google Cloud Dataflow | share | Leans |
|---|---|---|---|---|---|
| United States | 88 | 70% | 209 | 58% | Apache Storm |
| Canada | 5 | 4% | 10 | 3% | even |
| United Kingdom | 5 | 4% | 30 | 8% | Google Cloud Dataflow |
| France | 4 | 3% | 16 | 4% | even |
| Germany | 3 | 2% | 13 | 4% | even |
| Poland | 3 | 2% | 6 | 2% | even |
| China | 2 | 2% | – | – | outside top 12 |
| India | 2 | 2% | 15 | 4% | Google Cloud Dataflow |
| Netherlands | 2 | 2% | – | – | outside top 12 |
| Singapore | 2 | 2% | – | – | outside top 12 |
| United Arab Emirates | 1 | 1% | – | – | outside top 12 |
| BD | 1 | 1% | – | – | outside top 12 |
| Sweden | – | – | 10 | 3% | outside top 12 |
| Spain | – | – | 6 | 2% | outside top 12 |
| Australia | – | – | 5 | 1% | outside top 12 |
| Belgium | – | – | 4 | 1% | outside top 12 |
| Brazil | – | – | 4 | 1% | outside top 12 |
| Segment | Apache Storm | share | Google Cloud Dataflow | share | Leans |
|---|---|---|---|---|---|
| Data & AI | 304 | 43% | 1,141 | 64% | Google Cloud Dataflow |
| Engineering (non-software) | 146 | 21% | 4 | 0% | Apache Storm |
| Software engineering | 138 | 20% | 266 | 15% | Apache Storm |
| Construction and civil | 19 | 3% | – | – | outside top 12 |
| IT operations & business systems | 16 | 2% | 87 | 5% | Google Cloud Dataflow |
| Product, program & project management | 13 | 2% | 14 | 1% | even |
| Administration & office | 1 | 0% | – | – | outside top 12 |
| Design & UX | 1 | 0% | – | – | outside top 12 |
| Research and science | 1 | 0% | – | – | outside top 12 |
| Healthcare clinical | – | – | 29 | 2% | outside top 12 |
| Sales | – | – | 13 | 1% | outside top 12 |
| Finance & accounting | – | – | 6 | 0% | outside top 12 |
| Customer service & success | – | – | 4 | 0% | outside top 12 |
| Human resources | – | – | 3 | 0% | outside top 12 |
| Education & training | – | – | 2 | 0% | outside top 12 |
| Unclassified | – | – | 2 | 0% | outside top 12 |
The companies behind each column
Companies using Apache Storm →
Companies using Google Cloud Dataflow →
distributed processing ranked →
Quote the sentence with the date and the link. The numbers change daily; the link always shows the current ones.
Google Cloud Dataflow is named by 362 companies in job postings and Apache Storm by 125; 0 name both. (Breaknorm, 30 October 2026, https://breaknorm.co/compare/apache-storm-vs-google-cloud-dataflow)
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 Storm vs Google Cloud Dataflow: questions
Which is more used, Apache Storm or Google Cloud Dataflow?
By companies naming it in their own job postings, Google Cloud Dataflow (362) over Apache Storm (125). By website-and-DNS footprint, Google Cloud Dataflow (0 vs 0), because its scripts and mail records sit on many small company sites.
Who chooses Apache Storm?
40% of Apache Storm companies have 2 to 200 employees, against 38% for Google Cloud Dataflow. 37% of Apache Storm companies have over 1,000 employees, against 38% for Google Cloud Dataflow.
Do companies run both?
0 companies name both in their postings, usually Apache Storm in marketing and Google Cloud Dataflow 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
The same data as a search, over MCP and the API, as bulk files, or pushed to you as it changes.
Every company on either tool,
with the person who owns it
Filter on Apache Storm or Google Cloud Dataflow. Start free, no card.