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Index › Products › Snowflake Data Clean Rooms · October 2026 Edition
Snowflake Data Cloud · 1 category · Ranked

Snowflake Data Clean Rooms

158Judge labels
31First choices
25Negative labels
14 / 14Models named it
1Category
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10-05.2, every buyer segment counted.
Best standing
38% in Data clean rooms for enterprise buyers
Rank 1 of 100 in the mid-market standingaccepted challenger
6 of 14 models made it the first choice on the direct prompt; 10% of its 52 labels there were negative.
What the models named instead of Snowflake Data Clean Rooms →
By buyer segmentStrongest at enterprise.
In data clean rooms · each standing computed within its segment · bars are 0 to 100 · the accent bar is the product's own best reading

Standing by category

Every category where a model named Snowflake Data Clean Rooms for a mid-market B2B company. Share is first choices across the direct, paraphrase, budget and scale prompts; rank is within every product named in that category.
CategoryFunctionShareRankNegative rateLabelsQuadrantSince September 2026
Data clean roomsGTM data and infrastructure19%1 of 10010%52accepted challenger

Movement

This is the first edition on this tier, so no move can be computed for Snowflake Data Clean Rooms yet. From the next edition this section shows, per buyer segment and per category, whether its share moved by more than the measured noise floor.

By model

How each model treated Snowflake Data Clean Rooms across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
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ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.521104
GPT-5.4 mini13105
Gemini 3.5 Flash15006
Perplexity Sonar21003
Grok 4.1 Fast22015
Mistral Small01102
DeepSeek V4 Flash03025
Llama 4 Maverick00202
Qwen 3.7 Flash21104
Kimi K202114
GLM 4.7 FlashX21104
MiniMax M2.500101
GPT-6 Luna12014
Muse Glimmer 30B30003

By framing

Which of the six questions produced the naming. By model says how often; this says asked what. The first-choice count on the right carries the marks of the models that produced it.
FramingLabels by classFirst choices
Direct31 labels10
Paraphrase24 labels9
Comparative36 labels15not counted in share
Budget-constrained29 labels10
Scale-constrained19 labels2
Negative19 labelsNone
First choiceAlternativeMentionNegative158 labels in all, every segment counted; 31 of the 46 first choices count toward share, since the comparative and negative framings do not. The bar is one segment per label class, to scale within the framing.

What the models said for it

Verbatim evidence the judge attached to positive labels.

“Choose Snowflake, Databricks, or AWS if you already have a mature data team, store most of your data in these warehouses” Gemini 3.5 Flash · Data clean rooms · comparative prompt · first choice
“Start with Snowflake Secure Data Sharing/Clean Rooms. It offers the highest probability of successful collaborations” Qwen 3.7 Flash · Data clean rooms · paraphrase prompt · first choice
“Choose Snowflake if you are a data-led organization that needs to run complex SQL queries, ensure strict data governance” GLM 4.7 FlashX · Data clean rooms · comparative prompt · first choice
“For your size, warehouse-native DCRs often offer the best fit—low friction if you're already on Snowflake/BigQuery.” Grok 4.1 Fast · Data clean rooms · scale prompt · first choice

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.

“Usage-based through Snowflake consumption; costs scale with data volume” Kimi K2 · Data clean rooms · budget prompt · hard negative
“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
“Snowflake and AWS Clean Rooms get reasonable marks when properly configured — but watch for the cost/complexity pitfalls” DeepSeek V4 Flash · Data clean rooms · negative prompt · soft negative
“Skip a neutral or enterprise clean room (like Snowflake, LiveRamp, or InfoSum) for now” DeepSeek V4 Flash · Data clean rooms · budget prompt · soft negative

Named alongside

The products named in the same answers as Snowflake Data Clean Rooms, over the 158 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Snowflake Data Clean Rooms was named but was not.
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ProductSame answerTook the first choice insteadHead to head
LiveRamp Clean Room95 of 1586Not among the top eight
Habu39 of 1582Compare →
Meta Advanced Analytics30 of 1580Not among the top eight
Optable19 of 1584Not among the top eight
A head-to-head page exists where both products are among a category's top eight. The other rows are the same fact without a page behind them, so they link to the product instead.

What carried it into the answer

The sites and pages cited by the answers that named Snowflake Data Clean Rooms. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 152 of the 158 answers that named Snowflake Data Clean Rooms and are not a share of its labels.

Domains cited

decentriq.com86
guideflow.com72
digitalapplied.com70
liveramp.com59
docs.snowflake.comYour site57
us.fitgap.com56
aws.amazon.com55
gartner.com48
snowflake.comYour site46
aiopsschool.com43

489 of the 592 domain citations in answers naming Snowflake Data Clean Rooms came from somebody else's page.

Pages cited

Pages are listed as the models cited them.

Search and answers

Where Snowflake Data Clean Rooms stands in Google search beside where it stands in the models' answers.
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In search

Google, US estimates
Position for “data clean room”
–
not in the top ten
Position for “best data clean room”
6
Searches for its name, Google
390 a month (“snowflake data clean rooms”)
AI search demand for its name, est.
11 a month
Its company's site
snowflake.com shared with Snowflake Data Cloud's other products; the figures are the site's
Organic visits to its site
about 718,749 a month
Searches its site ranks for
40,654 · 5,633 in the top three
Sites linking to it
27,971
Paid Google search
1 searches its ads show for, about 2 clicks and $0 a month (estimate)
Ads on GoogleDetailLess
118+ ads · 94 text, 21 image, 3 video · 118 shown in the last 30 days

First shown January 2022, as Snowflake Inc., verified. Ads started 2025-10 to 2026-09: 60 in the year, 58 before. 2 more by other advertisers linking to it.

On Google's pages: 1 2 3 4

In answers

This edition
Share of first choices
19%
rank 1 of 100 in data clean rooms
First choices
31
across its categories
Named in
158 answers
Its own site cited
in 152 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 Snowflake Data Clean Rooms

What the judge wrote, as written, with how often. The vendor table decides that these count as Snowflake Data Clean Rooms; a claim can dispute any of them.
Snowflake 19Snowflake Clean Rooms 4Snowflake Data Clean Room 3Snowflake (Clean Rooms) 1Snowflake + Crystal 1Snowflake Data Clean Rooms (formerly Samooha) 1

Follow Snowflake Data 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

Snowflake Inc. is the company behind Snowflake Data Clean Rooms.
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On record

Wikidata
Headquarters
San Mateo, United States
Founded
2012
Employees
about 1,400 (2019)
Ownership
Public, SNOW on New York Stock Exchange
Also from Snowflake Data Cloud
Snowflake Data Clean Room

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

Is this your product?

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 Snowflake Data 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 Snowflake Data 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 Snowflake Data Clean Rooms by email, built from the raw record of the edition. It shows:

  • where Snowflake Data 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 Snowflake Data 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.
The subscriber app

A verification link goes to your work email; an address at snowflake.com is approved on the spot, any other is reviewed by hand. Your email is never published. Claiming gives no say over labels, shares, verdicts or which quotes appear.

Badges

Wins only: a badge exists where Snowflake Data Clean Rooms is ranked in a category's top three this edition. Three sizes, one file each, light and dark; the code is under each.
ShowHide

AI models recommend Snowflake Data Clean Rooms first in Data clean rooms this edition. Each badge says so in the buyer's words, names the edition, and links to the standing. The next edition issues a new badge; this one stays true as a record of October 2026.

Wide · 320 × 104 Website, beside other badges
AI models' first choice in Data clean rooms, October 2026 Edition, GTM AI Recommendation Index
Show the code
<a href="https://gtm-ai-index.com/gtm-data/data-clean-rooms/"><img src="https://gtm-ai-index.com/badges/2026-10/snowflake-data-clean-rooms--data-clean-rooms-wide.svg" alt="AI models' first choice in Data clean rooms, October 2026 Edition, GTM AI Recommendation Index" width="320" height="104"></a>

Copy the code as it is. The link is part of the badge: it points at the Data clean rooms standing, where the claim can be checked.

Square · 240 × 240 LinkedIn, slides
AI models' first choice in Data clean rooms, October 2026 Edition, GTM AI Recommendation Index
Show the code
<a href="https://gtm-ai-index.com/gtm-data/data-clean-rooms/"><img src="https://gtm-ai-index.com/badges/2026-10/snowflake-data-clean-rooms--data-clean-rooms-square.svg" alt="AI models' first choice in Data clean rooms, October 2026 Edition, GTM AI Recommendation Index" width="240" height="240"></a>

Copy the code as it is. The link is part of the badge: it points at the Data clean rooms standing, where the claim can be checked.

Compact · 200 × 56 Email signature, footer
AI models' first choice in Data clean rooms, October 2026 Edition, GTM AI Recommendation Index
Show the code
<a href="https://gtm-ai-index.com/gtm-data/data-clean-rooms/"><img src="https://gtm-ai-index.com/badges/2026-10/snowflake-data-clean-rooms--data-clean-rooms-compact.svg" alt="AI models' first choice in Data clean rooms, October 2026 Edition, GTM AI Recommendation Index" width="200" height="56"></a>

Copy the code as it is. The link is part of the badge: it points at the Data clean rooms standing, where the claim can be checked.

Badges read on light and dark pages. Alt text carries the claim, the category, the edition and the index, so it stays a citation where the image does not load.