Dagster VS Databricks Workflows
As of 4 November 2026, Databricks Workflows is named by 293 companies and Dagster by 884; Dagster skews to companies under 200 people (53% vs 28%), Databricks Workflows to companies over 1,000 (47% vs 21%).
As of 4 November 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: Dagster's script and mail records show on hundreds of thousands of small sites, Databricks Workflows rarely leaves a trace outside its own apps. Compare on the job-posting numbers; use the footprint for reach.
- Dagster: 2–200 employees
- 53%
- Databricks Workflows: 2–200 employees
- 28%
- Dagster: 1,000+ employees
- 21%
- Databricks Workflows: 1,000+ employees
- 47%
- Postings per company, 90 days
- 1.8 · 2.8
- 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 | Dagster | share | Databricks Workflows | share | Leans |
|---|---|---|---|---|---|
| Self-employed | 35 | 4% | 5 | 2% | Dagster |
| 2-10 employees | 106 | 12% | 12 | 4% | Dagster |
| 11-50 employees | 155 | 18% | 26 | 9% | Dagster |
| 51-200 employees | 204 | 23% | 45 | 15% | Dagster |
| 201-500 employees | 111 | 13% | 38 | 13% | even |
| 501-1000 employees | 91 | 10% | 30 | 10% | even |
| 1001-5000 employees | 110 | 12% | 49 | 17% | Databricks Workflows |
| 5001-10000 employees | 25 | 3% | 23 | 8% | Databricks Workflows |
| 10,001+ employees | 47 | 5% | 65 | 22% | Databricks Workflows |
| Segment | Dagster | share | Databricks Workflows | share | Leans |
|---|---|---|---|---|---|
| Technology & software | 449 | 51% | 117 | 40% | Dagster |
| Business & finance services | 198 | 22% | 75 | 26% | Databricks Workflows |
| Manufacturing & industry | 61 | 7% | 31 | 11% | Databricks Workflows |
| Media & content | 35 | 4% | 8 | 3% | even |
| Public, community & associations | 26 | 3% | – | – | outside top 12 |
| Consumer services & leisure | 23 | 3% | 9 | 3% | even |
| Commerce & trade | 21 | 2% | 15 | 5% | Databricks Workflows |
| Utilities & infrastructure | 20 | 2% | 6 | 2% | even |
| Health care | 15 | 2% | 10 | 3% | even |
| Property & construction | 10 | 1% | 3 | 1% | even |
| Transport, logistics & rental | 10 | 1% | 5 | 2% | even |
| Hospitality & travel | 7 | 1% | 5 | 2% | even |
| Automotive | – | – | 7 | 2% | outside top 12 |
| Segment | Dagster | share | Databricks Workflows | share | Leans |
|---|---|---|---|---|---|
| United States | 585 | 66% | 185 | 63% | Dagster |
| United Kingdom | 64 | 7% | 19 | 6% | even |
| Germany | 27 | 3% | 5 | 2% | even |
| France | 26 | 3% | 8 | 3% | even |
| Canada | 22 | 2% | 8 | 3% | even |
| Netherlands | 14 | 2% | – | – | outside top 12 |
| Brazil | 12 | 1% | 6 | 2% | even |
| Sweden | 12 | 1% | 5 | 2% | even |
| Australia | 11 | 1% | – | – | outside top 12 |
| India | 7 | 1% | – | – | outside top 12 |
| Switzerland | 6 | 1% | 4 | 1% | even |
| Poland | 6 | 1% | 4 | 1% | even |
| Denmark | – | – | 5 | 2% | outside top 12 |
| Romania | – | – | 4 | 1% | outside top 12 |
| Singapore | – | – | 4 | 1% | outside top 12 |
| Segment | Dagster | share | Databricks Workflows | share | Leans |
|---|---|---|---|---|---|
| Data & AI | 1,608 | 79% | 791 | 84% | Databricks Workflows |
| Software engineering | 254 | 12% | 46 | 5% | Dagster |
| IT operations & business systems | 15 | 1% | 16 | 2% | even |
| Product, program & project management | 9 | 0% | 6 | 1% | even |
| Unclassified | 7 | 0% | – | – | outside top 12 |
| General management & consulting | 5 | 0% | 1 | 0% | even |
| Research and science | 5 | 0% | – | – | outside top 12 |
| Sales | 4 | 0% | 2 | 0% | even |
| Engineering (non-software) | 3 | 0% | 1 | 0% | even |
| Customer service & success | 2 | 0% | 1 | 0% | even |
| Finance & accounting | 2 | 0% | 7 | 1% | even |
| Logistics warehouse and transport | 2 | 0% | – | – | outside top 12 |
| Marketing & communications | 2 | 0% | – | – | outside top 12 |
| Business development & strategy | 1 | 0% | – | – | outside top 12 |
| Hospitality and food service | – | – | 1 | 0% | outside top 12 |
| Quality, safety & environment | – | – | 1 | 0% | outside top 12 |
The companies behind each column
Companies using Dagster →
Companies using Databricks Workflows →
data orchestration ranked →
Quote the sentence with the date and the link. The numbers change daily; the link always shows the current ones.
Databricks Workflows is named by 293 companies in job postings and Dagster by 884; 0 name both. (Breaknorm, 4 November 2026, https://breaknorm.co/compare/dagster-vs-databricks-workflows)
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.
Dagster vs Databricks Workflows: questions
Which is more used, Dagster or Databricks Workflows?
By companies naming it in their own job postings, Dagster (884) over Databricks Workflows (293). By website-and-DNS footprint, Databricks Workflows (0 vs 0), because its scripts and mail records sit on many small company sites.
Who chooses Dagster?
53% of Dagster companies have 2 to 200 employees, against 28% for Databricks Workflows. 21% of Dagster companies have over 1,000 employees, against 47% for Databricks Workflows.
Do companies run both?
0 companies name both in their postings, usually Dagster in marketing and Databricks Workflows 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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