Web Ontology Language VS WSDL
As of 30 October 2026, WSDL is named by 171 companies and Web Ontology Language by 154; Web Ontology Language skews to companies under 200 people (39% vs 50%), WSDL to companies over 1,000 (30% 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: Web Ontology Language's script and mail records show on hundreds of thousands of small sites, WSDL rarely leaves a trace outside its own apps. Compare on the job-posting numbers; use the footprint for reach.
- Web Ontology Language: 2–200 employees
- 39%
- WSDL: 2–200 employees
- 50%
- Web Ontology Language: 1,000+ employees
- 39%
- WSDL: 1,000+ employees
- 30%
- Postings per company, 90 days
- 3.0 · 2.6
- 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 | Web Ontology Language | share | WSDL | share | Leans |
|---|---|---|---|---|---|
| 2-10 employees | 16 | 10% | 5 | 3% | Web Ontology Language |
| 11-50 employees | 25 | 16% | 34 | 20% | WSDL |
| 51-200 employees | 19 | 12% | 47 | 27% | WSDL |
| 201-500 employees | 24 | 16% | 19 | 11% | Web Ontology Language |
| 501-1000 employees | 10 | 6% | 13 | 8% | even |
| 1001-5000 employees | 27 | 18% | 25 | 15% | Web Ontology Language |
| 5001-10000 employees | 7 | 5% | 7 | 4% | even |
| 10,001+ employees | 26 | 17% | 19 | 11% | Web Ontology Language |
| Self-employed | – | – | 2 | 1% | outside top 12 |
| Segment | Web Ontology Language | share | WSDL | share | Leans |
|---|---|---|---|---|---|
| Technology & software | 77 | 50% | 108 | 63% | WSDL |
| Business & finance services | 22 | 14% | 32 | 19% | WSDL |
| Manufacturing & industry | 15 | 10% | 9 | 5% | Web Ontology Language |
| Public, community & associations | 13 | 8% | 4 | 2% | Web Ontology Language |
| Media & content | 7 | 5% | 3 | 2% | Web Ontology Language |
| Consumer services & leisure | 5 | 3% | 3 | 2% | even |
| Property & construction | 4 | 3% | 1 | 1% | Web Ontology Language |
| Utilities & infrastructure | 3 | 2% | 4 | 2% | even |
| Commerce & trade | 2 | 1% | 2 | 1% | even |
| Health care | 2 | 1% | – | – | outside top 12 |
| Transport, logistics & rental | 2 | 1% | 3 | 2% | even |
| Automotive | 1 | 1% | 1 | 1% | even |
| Hospitality & travel | – | – | 1 | 1% | outside top 12 |
| Segment | Web Ontology Language | share | WSDL | share | Leans |
|---|---|---|---|---|---|
| United States | 69 | 45% | 110 | 64% | WSDL |
| Germany | 29 | 19% | 4 | 2% | Web Ontology Language |
| United Kingdom | 13 | 8% | 9 | 5% | Web Ontology Language |
| France | 4 | 3% | 2 | 1% | even |
| India | 4 | 3% | 7 | 4% | even |
| United Arab Emirates | 3 | 2% | – | – | outside top 12 |
| Belgium | 3 | 2% | – | – | outside top 12 |
| Poland | 3 | 2% | 5 | 3% | even |
| Singapore | 3 | 2% | – | – | outside top 12 |
| BD | 2 | 1% | – | – | outside top 12 |
| Canada | 2 | 1% | 5 | 3% | even |
| Switzerland | 2 | 1% | – | – | outside top 12 |
| Netherlands | – | – | 5 | 3% | outside top 12 |
| Italy | – | – | 4 | 2% | outside top 12 |
| Czechia | – | – | 3 | 2% | outside top 12 |
| Spain | – | – | 2 | 1% | outside top 12 |
| QA | – | – | 2 | 1% | outside top 12 |
| Segment | Web Ontology Language | share | WSDL | share | Leans |
|---|---|---|---|---|---|
| Data & AI | 242 | 44% | 23 | 2% | Web Ontology Language |
| Software engineering | 91 | 16% | 704 | 59% | WSDL |
| IT operations & business systems | 24 | 4% | 172 | 14% | WSDL |
| Finance & accounting | 8 | 1% | – | – | outside top 12 |
| Research and science | 8 | 1% | – | – | outside top 12 |
| Skilled trades and field service | 8 | 1% | – | – | outside top 12 |
| General management & consulting | 6 | 1% | 5 | 0% | even |
| Healthcare clinical | 5 | 1% | – | – | outside top 12 |
| Logistics warehouse and transport | 5 | 1% | – | – | outside top 12 |
| Engineering (non-software) | 4 | 1% | 6 | 1% | even |
| Marketing & communications | 4 | 1% | – | – | outside top 12 |
| Product, program & project management | 4 | 1% | 7 | 1% | even |
| Unclassified | – | – | 45 | 4% | outside top 12 |
| Design & UX | – | – | 21 | 2% | outside top 12 |
| Sales | – | – | 6 | 1% | outside top 12 |
| Administration & office | – | – | 4 | 0% | outside top 12 |
| Arts media and entertainment | – | – | 4 | 0% | outside top 12 |
| Human resources | – | – | 4 | 0% | outside top 12 |
The companies behind each column
Companies using Web Ontology Language →
Companies using WSDL →
api specs data formats ranked →
Quote the sentence with the date and the link. The numbers change daily; the link always shows the current ones.
WSDL is named by 171 companies in job postings and Web Ontology Language by 154; 0 name both. (Breaknorm, 30 October 2026, https://breaknorm.co/compare/owl-vs-wsdl)
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.
Web Ontology Language vs WSDL: questions
Which is more used, Web Ontology Language or WSDL?
By companies naming it in their own job postings, WSDL (171) over Web Ontology Language (154). By website-and-DNS footprint, WSDL (0 vs 0), because its scripts and mail records sit on many small company sites.
Who chooses Web Ontology Language?
39% of Web Ontology Language companies have 2 to 200 employees, against 50% for WSDL. 39% of Web Ontology Language companies have over 1,000 employees, against 30% for WSDL.
Do companies run both?
0 companies name both in their postings, usually Web Ontology Language in marketing and WSDL 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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Every company on either tool,
with the person who owns it
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