Databricks · 1 category · RankedDatabricks Clean Rooms
Standing by category
| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Data clean rooms | GTM data and infrastructure | 2% | 10 of 100 | 15% | 27 | accepted challenger |
Movement
By model
How each model treated Databricks Clean Rooms across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.ShowHide
By model
| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 1 | 1 | 1 | 0 | 3 |
| GPT-5.4 mini | 0 | 1 | 1 | 0 | 2 |
| Gemini 3.5 Flash | 1 | 3 | 1 | 0 | 5 |
| Perplexity Sonar | 0 | 0 | 0 | 0 | 0 |
| Grok 4.1 Fast | 0 | 0 | 2 | 2 | 4 |
| Mistral Small | 0 | 0 | 0 | 0 | 0 |
| DeepSeek V4 Flash | 0 | 1 | 1 | 1 | 3 |
| Llama 4 Maverick | 0 | 0 | 2 | 0 | 2 |
| Qwen 3.7 Flash | 0 | 0 | 1 | 0 | 1 |
| Kimi K2 | 0 | 0 | 1 | 1 | 2 |
| GLM 4.7 FlashX | 0 | 0 | 2 | 0 | 2 |
| MiniMax M2.5 | 0 | 0 | 1 | 0 | 1 |
| GPT-6 Luna | 0 | 1 | 0 | 0 | 1 |
| Muse Glimmer 30B | 0 | 1 | 0 | 0 | 1 |
By framing
What the models said for it
Verbatim evidence the judge attached to positive labels.
“Snowflake, Databricks, and LiveRamp Safe Haven provide balanced scalability and governance support.” Claude Haiku 4.5 · Data clean rooms · direct prompt · first choice
“Choose Snowflake, Databricks, or AWS if you already have a mature data team” Gemini 3.5 Flash · Data clean rooms · comparative prompt · first choice
“If your data ecosystem is built on Databricks, their Delta Sharing and Unity Catalog offer a similar, highly secure distributed data clean room experience.” Gemini 3.5 Flash · Data clean rooms · paraphrase prompt · alternative
“Warehouse-native alternative. Data scientists; Native integration with Unity Catalog for governance. Requires technical proficiency.” Muse Glimmer 30B · Data clean rooms · comparative prompt · alternative
And against it
Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.
“Cloud-based (e.g., AWS Clean Rooms, Snowflake, Databricks) | Strong infrastructure, but integration complexity and variable TCO” Grok 4.1 Fast · Data clean rooms · negative prompt · soft negative
“Some concerns about identity resolution rules not being well-documented” Kimi K2 · Data clean rooms · negative prompt · soft negative
“user reviews of Databricks Clean Rooms have scored poorly here” DeepSeek V4 Flash · Data clean rooms · negative prompt · soft negative
“Enterprise giants (e.g., full Databricks) suit larger ops.” Grok 4.1 Fast · Data clean rooms · direct prompt · soft negative
Named alongside
The products named in the same answers as Databricks Clean Rooms, over the 73 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Databricks Clean Rooms was named but was not.ShowHide
Named alongside
What carried it into the answer
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 72 of the 73 answers that named Databricks Clean Rooms and are not a share of its labels.
Domains cited
291 of the 291 domain citations in answers naming Databricks Clean Rooms came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Search and answers
databricks.com ranks 3 on Google for the category's searches. In the answers, Databricks Clean Rooms takes 2% of first choices and Snowflake Data Clean Rooms takes 19%.ShowHide
Search and answers
In search
Google, US estimates- Searches for its name, Google
- 260 a month (“databricks clean rooms”)
- AI search demand for its name, est.
- 4 a month
- Its company's site
- databricks.com shared with Databricks's other products; the figures are the site's
- Organic visits to its site
- about 689,756 a month
- Searches its site ranks for
- 43,327 · 6,682 in the top three
- Sites linking to it
- 33,328
- Paid Google search
- 33 searches its ads show for, about 570 clicks and $34,664 a month (estimate)
In answers
This edition- First choices
- 1 across its categories
- Named in
- 73 answers
- Its own site cited
- in 72 of the answers that named it
Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.
Names read as Databricks Clean Rooms
Follow Databricks Clean Rooms
An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.
Already following? Everything you follow, with a stop for each.
The company
Databricks is the company behind Databricks Clean Rooms.ShowHide
The company
On record
Wikidata- Website
- databricks.com
- Headquarters
- San Francisco, United States
- Founded
- 2013
- Employees
- about 4,000 (2022)
Fetched September 14, 2026. These describe the company, not the product's standing, and a claimed page can dispute any of them. · Wikidata · LinkedIn · Crunchbase
Claim this page
Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when Databricks Clean Rooms's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as Databricks Clean Rooms, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
What a new claim receivesHide what a new claim receives
A new claim receives the current edition's vendor brief for Databricks Clean Rooms by email, built from the raw record of the edition. It shows:
- where Databricks Clean Rooms is named, by buyer and by framing, and which cells hold its first choices;
- the claims the models make when they name it, ranked, with the strongest and the weakest quoted;
- its vocabulary against the segment leader's, and the pages the models cited;
- who was chosen in the answers that did not name Databricks Clean Rooms, and every reason the record gives;
- a battlecard for each top rival: the head-to-head split, why they win, and the reservation quoted against them;
- one page of published figures cleared to show a buyer.