Google Cloud Dataproc VS PySpark
As of 30 October 2026, PySpark is named by 1,730 companies and Google Cloud Dataproc by 131; Google Cloud Dataproc skews to companies under 200 people (27% vs 34%), PySpark to companies over 1,000 (40% vs 47%).
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: Google Cloud Dataproc's script and mail records show on hundreds of thousands of small sites, PySpark rarely leaves a trace outside its own apps. Compare on the job-posting numbers; use the footprint for reach.
- Google Cloud Dataproc: 2–200 employees
- 27%
- PySpark: 2–200 employees
- 34%
- Google Cloud Dataproc: 1,000+ employees
- 47%
- PySpark: 1,000+ employees
- 40%
- Postings per company, 90 days
- 3.7 · 3.5
- 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 | Google Cloud Dataproc | share | PySpark | share | Leans |
|---|---|---|---|---|---|
| Self-employed | 1 | 1% | 15 | 1% | even |
| 2-10 employees | 5 | 4% | 91 | 5% | even |
| 11-50 employees | 10 | 8% | 182 | 11% | PySpark |
| 51-200 employees | 21 | 16% | 323 | 19% | PySpark |
| 201-500 employees | 21 | 16% | 245 | 14% | even |
| 501-1000 employees | 11 | 8% | 179 | 10% | even |
| 1001-5000 employees | 23 | 18% | 308 | 18% | even |
| 5001-10000 employees | 6 | 5% | 96 | 6% | even |
| 10,001+ employees | 33 | 25% | 291 | 17% | Google Cloud Dataproc |
| Segment | Google Cloud Dataproc | share | PySpark | share | Leans |
|---|---|---|---|---|---|
| Technology & software | 72 | 55% | 804 | 46% | Google Cloud Dataproc |
| Business & finance services | 30 | 23% | 439 | 25% | PySpark |
| Manufacturing & industry | 6 | 5% | 153 | 9% | PySpark |
| Utilities & infrastructure | 5 | 4% | 43 | 2% | even |
| Media & content | 4 | 3% | 50 | 3% | even |
| Commerce & trade | 3 | 2% | 58 | 3% | even |
| Consumer services & leisure | 3 | 2% | 37 | 2% | even |
| Health care | 3 | 2% | 38 | 2% | even |
| Public, community & associations | 2 | 2% | 38 | 2% | even |
| Hospitality & travel | 1 | 1% | – | – | outside top 12 |
| Property & construction | 1 | 1% | 19 | 1% | even |
| Transport, logistics & rental | 1 | 1% | 25 | 1% | even |
| Automotive | – | – | 12 | 1% | outside top 12 |
| Segment | Google Cloud Dataproc | share | PySpark | share | Leans |
|---|---|---|---|---|---|
| United States | 85 | 65% | 1,001 | 58% | Google Cloud Dataproc |
| United Kingdom | 8 | 6% | 148 | 9% | PySpark |
| India | 6 | 5% | 50 | 3% | even |
| Canada | 5 | 4% | 65 | 4% | even |
| Germany | 4 | 3% | 79 | 5% | even |
| Poland | 4 | 3% | 22 | 1% | even |
| France | 3 | 2% | 51 | 3% | even |
| Brazil | 2 | 2% | 29 | 2% | even |
| Spain | 2 | 2% | 21 | 1% | even |
| Singapore | 2 | 2% | – | – | outside top 12 |
| Austria | 1 | 1% | – | – | outside top 12 |
| Australia | 1 | 1% | 25 | 1% | even |
| Netherlands | – | – | 39 | 2% | outside top 12 |
| Sweden | – | – | 20 | 1% | outside top 12 |
| Segment | Google Cloud Dataproc | share | PySpark | share | Leans |
|---|---|---|---|---|---|
| Data & AI | 433 | 67% | 5,814 | 76% | PySpark |
| Software engineering | 69 | 11% | 688 | 9% | even |
| IT operations & business systems | 40 | 6% | 225 | 3% | Google Cloud Dataproc |
| Hospitality and food service | 4 | 1% | – | – | outside top 12 |
| Product, program & project management | 3 | 0% | 52 | 1% | even |
| Sales | 3 | 0% | 26 | 0% | even |
| Finance & accounting | 2 | 0% | 35 | 0% | even |
| General management & consulting | 2 | 0% | 48 | 1% | even |
| Customer service & success | 1 | 0% | – | – | outside top 12 |
| Education & training | 1 | 0% | – | – | outside top 12 |
| Engineering (non-software) | 1 | 0% | 35 | 0% | even |
| Legal, compliance & risk | 1 | 0% | 42 | 1% | even |
| Unclassified | – | – | 20 | 0% | outside top 12 |
| Marketing & communications | – | – | 15 | 0% | outside top 12 |
| Construction and civil | – | – | 11 | 0% | outside top 12 |
The companies behind each column
Companies using Google Cloud Dataproc →
Companies using PySpark →
distributed processing ranked →
Quote the sentence with the date and the link. The numbers change daily; the link always shows the current ones.
PySpark is named by 1,730 companies in job postings and Google Cloud Dataproc by 131; 133 name both. (Breaknorm, 30 October 2026, https://breaknorm.co/compare/google-cloud-dataproc-vs-pyspark)
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.
Google Cloud Dataproc vs PySpark: questions
Which is more used, Google Cloud Dataproc or PySpark?
By companies naming it in their own job postings, PySpark (1,730) over Google Cloud Dataproc (131). By website-and-DNS footprint, PySpark (0 vs 0), because its scripts and mail records sit on many small company sites.
Who chooses Google Cloud Dataproc?
27% of Google Cloud Dataproc companies have 2 to 200 employees, against 34% for PySpark. 47% of Google Cloud Dataproc companies have over 1,000 employees, against 40% for PySpark.
Do companies run both?
133 companies name both in their postings, usually Google Cloud Dataproc in marketing and PySpark 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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