Kafka Streams VS MapReduce
As of 30 October 2026, MapReduce is named by 192 companies and Kafka Streams by 109; Kafka Streams skews to companies under 200 people (32% vs 50%), MapReduce to companies over 1,000 (29% vs 39%).
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: Kafka Streams's script and mail records show on hundreds of thousands of small sites, MapReduce rarely leaves a trace outside its own apps. Compare on the job-posting numbers; use the footprint for reach.
- Kafka Streams: 2–200 employees
- 32%
- MapReduce: 2–200 employees
- 50%
- Kafka Streams: 1,000+ employees
- 39%
- MapReduce: 1,000+ employees
- 29%
- Postings per company, 90 days
- 2.7 · 2.9
- 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 | Kafka Streams | share | MapReduce | share | Leans |
|---|---|---|---|---|---|
| 2-10 employees | 6 | 6% | 5 | 3% | Kafka Streams |
| 11-50 employees | 10 | 9% | 36 | 19% | MapReduce |
| 51-200 employees | 19 | 17% | 55 | 29% | MapReduce |
| 201-500 employees | 14 | 13% | 22 | 11% | even |
| 501-1000 employees | 17 | 16% | 13 | 7% | Kafka Streams |
| 1001-5000 employees | 15 | 14% | 26 | 14% | even |
| 5001-10000 employees | 9 | 8% | 2 | 1% | Kafka Streams |
| 10,001+ employees | 19 | 17% | 28 | 15% | Kafka Streams |
| Self-employed | – | – | 5 | 3% | outside top 12 |
| Segment | Kafka Streams | share | MapReduce | share | Leans |
|---|---|---|---|---|---|
| Technology & software | 61 | 56% | 122 | 64% | MapReduce |
| Business & finance services | 22 | 20% | 34 | 18% | Kafka Streams |
| Manufacturing & industry | 6 | 6% | 15 | 8% | MapReduce |
| Commerce & trade | 4 | 4% | 1 | 1% | Kafka Streams |
| Hospitality & travel | 4 | 4% | 1 | 1% | Kafka Streams |
| Automotive | 3 | 3% | 3 | 2% | even |
| Utilities & infrastructure | 3 | 3% | 2 | 1% | even |
| Media & content | 2 | 2% | 2 | 1% | even |
| Transport, logistics & rental | 2 | 2% | – | – | outside top 12 |
| Consumer services & leisure | 1 | 1% | 4 | 2% | even |
| Health care | 1 | 1% | 3 | 2% | even |
| Public, community & associations | – | – | 5 | 3% | outside top 12 |
| Segment | Kafka Streams | share | MapReduce | share | Leans |
|---|---|---|---|---|---|
| United States | 70 | 64% | 156 | 81% | MapReduce |
| United Kingdom | 9 | 8% | 4 | 2% | Kafka Streams |
| Germany | 4 | 4% | 4 | 2% | even |
| India | 4 | 4% | 6 | 3% | even |
| Australia | 3 | 3% | 3 | 2% | even |
| Brazil | 2 | 2% | – | – | outside top 12 |
| France | 2 | 2% | – | – | outside top 12 |
| Japan | 2 | 2% | – | – | outside top 12 |
| Poland | 2 | 2% | – | – | outside top 12 |
| Sweden | 2 | 2% | – | – | outside top 12 |
| United Arab Emirates | 1 | 1% | 1 | 1% | even |
| Austria | 1 | 1% | 2 | 1% | even |
| Italy | – | – | 3 | 2% | outside top 12 |
| Singapore | – | – | 3 | 2% | outside top 12 |
| Switzerland | – | – | 1 | 1% | outside top 12 |
| Colombia | – | – | 1 | 1% | outside top 12 |
| Cyprus | – | – | 1 | 1% | outside top 12 |
| Segment | Kafka Streams | share | MapReduce | share | Leans |
|---|---|---|---|---|---|
| Software engineering | 191 | 52% | 244 | 19% | Kafka Streams |
| Data & AI | 106 | 29% | 839 | 66% | MapReduce |
| Engineering (non-software) | 13 | 4% | 5 | 0% | Kafka Streams |
| IT operations & business systems | 11 | 3% | 29 | 2% | even |
| Logistics warehouse and transport | 3 | 1% | 2 | 0% | even |
| Product, program & project management | 1 | 0% | 11 | 1% | even |
| Education & training | – | – | 5 | 0% | outside top 12 |
| Finance & accounting | – | – | 4 | 0% | outside top 12 |
| General management & consulting | – | – | 3 | 0% | outside top 12 |
| Human resources | – | – | 1 | 0% | outside top 12 |
| Sales | – | – | 1 | 0% | outside top 12 |
| Unclassified | – | – | 1 | 0% | outside top 12 |
The companies behind each column
Companies using Kafka Streams →
Companies using MapReduce →
distributed processing ranked →
Quote the sentence with the date and the link. The numbers change daily; the link always shows the current ones.
MapReduce is named by 192 companies in job postings and Kafka Streams by 109; 0 name both. (Breaknorm, 30 October 2026, https://breaknorm.co/compare/kafka-streams-vs-mapreduce)
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.
Kafka Streams vs MapReduce: questions
Which is more used, Kafka Streams or MapReduce?
By companies naming it in their own job postings, MapReduce (192) over Kafka Streams (109). By website-and-DNS footprint, MapReduce (0 vs 0), because its scripts and mail records sit on many small company sites.
Who chooses Kafka Streams?
32% of Kafka Streams companies have 2 to 200 employees, against 50% for MapReduce. 39% of Kafka Streams companies have over 1,000 employees, against 29% for MapReduce.
Do companies run both?
0 companies name both in their postings, usually Kafka Streams in marketing and MapReduce 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 Kafka Streams or MapReduce. Start free, no card.