Google Cloud Dataflow VS Kafka Streams
As of 30 October 2026, Kafka Streams is named by 109 companies and Google Cloud Dataflow by 362; Google Cloud Dataflow skews to companies under 200 people (38% vs 32%), Kafka Streams to companies over 1,000 (39% vs 38%).
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 Dataflow's script and mail records show on hundreds of thousands of small sites, Kafka Streams rarely leaves a trace outside its own apps. Compare on the job-posting numbers; use the footprint for reach.
- Google Cloud Dataflow: 2–200 employees
- 38%
- Kafka Streams: 2–200 employees
- 32%
- Google Cloud Dataflow: 1,000+ employees
- 38%
- Kafka Streams: 1,000+ employees
- 39%
- Postings per company, 90 days
- 3.6 · 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 | Google Cloud Dataflow | share | Kafka Streams | share | Leans |
|---|---|---|---|---|---|
| Self-employed | 3 | 1% | – | – | outside top 12 |
| 2-10 employees | 20 | 6% | 6 | 6% | even |
| 11-50 employees | 44 | 12% | 10 | 9% | Google Cloud Dataflow |
| 51-200 employees | 72 | 20% | 19 | 17% | Google Cloud Dataflow |
| 201-500 employees | 55 | 15% | 14 | 13% | Google Cloud Dataflow |
| 501-1000 employees | 30 | 8% | 17 | 16% | Kafka Streams |
| 1001-5000 employees | 57 | 16% | 15 | 14% | even |
| 5001-10000 employees | 19 | 5% | 9 | 8% | Kafka Streams |
| 10,001+ employees | 62 | 17% | 19 | 17% | even |
| Segment | Google Cloud Dataflow | share | Kafka Streams | share | Leans |
|---|---|---|---|---|---|
| Technology & software | 186 | 51% | 61 | 56% | Kafka Streams |
| Business & finance services | 76 | 21% | 22 | 20% | even |
| Commerce & trade | 21 | 6% | 4 | 4% | Google Cloud Dataflow |
| Manufacturing & industry | 21 | 6% | 6 | 6% | even |
| Utilities & infrastructure | 15 | 4% | 3 | 3% | even |
| Consumer services & leisure | 11 | 3% | 1 | 1% | Google Cloud Dataflow |
| Media & content | 11 | 3% | 2 | 2% | even |
| Public, community & associations | 6 | 2% | – | – | outside top 12 |
| Health care | 5 | 1% | 1 | 1% | even |
| Property & construction | 4 | 1% | – | – | outside top 12 |
| Transport, logistics & rental | 3 | 1% | 2 | 2% | even |
| Automotive | 2 | 1% | 3 | 3% | Kafka Streams |
| Hospitality & travel | – | – | 4 | 4% | outside top 12 |
| Segment | Google Cloud Dataflow | share | Kafka Streams | share | Leans |
|---|---|---|---|---|---|
| United States | 209 | 58% | 70 | 64% | Kafka Streams |
| United Kingdom | 30 | 8% | 9 | 8% | even |
| France | 16 | 4% | 2 | 2% | Google Cloud Dataflow |
| India | 15 | 4% | 4 | 4% | even |
| Germany | 13 | 4% | 4 | 4% | even |
| Canada | 10 | 3% | – | – | outside top 12 |
| Sweden | 10 | 3% | 2 | 2% | even |
| Spain | 6 | 2% | – | – | outside top 12 |
| Poland | 6 | 2% | 2 | 2% | even |
| Australia | 5 | 1% | 3 | 3% | even |
| Belgium | 4 | 1% | – | – | outside top 12 |
| Brazil | 4 | 1% | 2 | 2% | even |
| Japan | – | – | 2 | 2% | outside top 12 |
| United Arab Emirates | – | – | 1 | 1% | outside top 12 |
| Austria | – | – | 1 | 1% | outside top 12 |
| Segment | Google Cloud Dataflow | share | Kafka Streams | share | Leans |
|---|---|---|---|---|---|
| Data & AI | 1,141 | 64% | 106 | 29% | Google Cloud Dataflow |
| Software engineering | 266 | 15% | 191 | 52% | Kafka Streams |
| IT operations & business systems | 87 | 5% | 11 | 3% | even |
| Healthcare clinical | 29 | 2% | – | – | outside top 12 |
| Product, program & project management | 14 | 1% | 1 | 0% | even |
| Sales | 13 | 1% | – | – | outside top 12 |
| Finance & accounting | 6 | 0% | – | – | outside top 12 |
| Customer service & success | 4 | 0% | – | – | outside top 12 |
| Engineering (non-software) | 4 | 0% | 13 | 4% | Kafka Streams |
| Human resources | 3 | 0% | – | – | outside top 12 |
| Education & training | 2 | 0% | – | – | outside top 12 |
| Unclassified | 2 | 0% | – | – | outside top 12 |
| Logistics warehouse and transport | – | – | 3 | 1% | outside top 12 |
The companies behind each column
Companies using Google Cloud Dataflow →
Companies using Kafka Streams →
distributed processing ranked →
Quote the sentence with the date and the link. The numbers change daily; the link always shows the current ones.
Kafka Streams is named by 109 companies in job postings and Google Cloud Dataflow by 362; 0 name both. (Breaknorm, 30 October 2026, https://breaknorm.co/compare/google-cloud-dataflow-vs-kafka-streams)
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 Dataflow vs Kafka Streams: questions
Which is more used, Google Cloud Dataflow or Kafka Streams?
By companies naming it in their own job postings, Google Cloud Dataflow (362) over Kafka Streams (109). By website-and-DNS footprint, Kafka Streams (0 vs 0), because its scripts and mail records sit on many small company sites.
Who chooses Google Cloud Dataflow?
38% of Google Cloud Dataflow companies have 2 to 200 employees, against 32% for Kafka Streams. 38% of Google Cloud Dataflow companies have over 1,000 employees, against 39% for Kafka Streams.
Do companies run both?
0 companies name both in their postings, usually Google Cloud Dataflow in marketing and Kafka Streams 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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