Data clean rooms
Asked as “data clean room”, and as “privacy-safe data collaboration platform”, on behalf of a mid-market B2B software company. 59 first choices recorded across the direct, paraphrase, budget and scale prompts, six models each. Added to the September 2026 Edition; its answers are read by the distilled judge (ai-indexes-judge-qwen3-14b), not the claude-opus-5 judge of the earlier categories: how the two compare.
Standing · first-choice share
19%
Contested · AWS Clean Rooms 15%
19Snowflake Data Clean Rooms15AWS Clean Rooms14Amazon Marketing Cloud53others
19% of first choices, contested.
The standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all six models, for a mid-market B2B software company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince September 2026
01
Snowflake Data Clean Rooms19%10%52accepted challengernewNew since September 2026: not ranked then, 19% now.
Snowflake Data Clean Rooms19%10%52accepted challengernewNew since September 2026: not ranked then, 19% now.03Amazon Marketing Cloud14%17%24accepted challengernewNew since September 2026: not ranked then, 14% now.
05Google Ads Data Hub Lab in the set10%18%28accepted challengernewNew since September 2026: not ranked then, 10% now.
07
Databricks Clean Rooms2%15%27accepted challengernewNew since September 2026: not ranked then, 2% now.
Databricks Clean Rooms2%15%27accepted challengernewNew since September 2026: not ranked then, 2% now.09Meta Advanced Analytics2%12%16accepted challengernewNew since September 2026: not ranked then, 2% now.
10
LiveRamp Clean Room2%32%37criticized challengernewNew since September 2026: not ranked then, 2% now.
LiveRamp Clean Room2%32%37criticized challengernewNew since September 2026: not ranked then, 2% now.The floor is 12 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. How the floor is measured
Bars are the share of first choices, 0 to 100Every product with at least 10 labels here. Every product name links to its product page.
Google Ads Data Hub is made by Google, whose model Gemini 3.1 Pro is in the set. On the four share prompts that model made it the first choice zero times of 4; the other five models zero times of 20. Lab treatment is defined on the method page; the row is marked, not excluded.
Recommended versus criticized
Every product with at least 10 labels here, on both axes. The 30% line names a quadrant, not the verdict above: that one needs more than 40%.
Criticized challengerCriticized default
Negative label rate →
01A02
A03
04G05
0607H08
M09
10Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative30%
Key
01Snowflake Data Clean Rooms19%
Snowflake Data Clean Rooms19%02AWS Clean Rooms15%
03Amazon Marketing Cloud14%
04InfoSum10%
InfoSum10%05Google Ads Data Hub10%
06Decentriq3%
Decentriq3%07Databricks Clean Rooms2%
Databricks Clean Rooms2%08Habu2%
09Meta Advanced Analytics2%
10LiveRamp Clean Room2%
LiveRamp Clean Room2%What they warned about
A high negative share on a product with few labels is a warning. A low share on a product with many labels is salience, not sentiment.
InfoSum23%
9 of 39 labels negative · 7 of 6 models · 2 hard negative
“Avoid enterprise SaaS (e.g., LiveRamp, InfoSum) at $500+/month unless trialing.” Grok 4.20, budget prompt
Google Ads Data Hub
18%
5 of 28 labels negative · 5 of 6 models
“Platform-owned environments such as Google Ads Data Hub, Amazon Marketing Cloud and Meta’s PET-based collaborations are widely adopted but raise lock-in, portability and conflict-of-interest questions.” Muse Glimmer 30B, negative prompt
LiveRamp Clean Room32%
12 of 37 labels negative · 4 of 6 models · 3 hard negative
“What to Avoid as a Mid-Market B2B - **LiveRamp / Habu:** Enterprise-grade, with the average enterprise setup running around **$879K**” DeepSeek V4 Flash, direct prompt
Snowflake Data Clean Rooms10%
5 of 52 labels negative · 4 of 6 models · 1 hard negative
“Usage-based through Snowflake consumption; costs scale with data volume” Kimi K2, budget prompt
What they cite
Citations exist only for the models that return a source list: fourteen of the six in this edition.
Sites the answers cite
79 of 84 answers in this category came back with a source list, from 14 of 6 models: citations where the model returns them, or the search results it consulted. 1097 links across 235 sites, every framing counted. Ranked by the number of answers carrying the site or page.
vendor site · Decentriq44 answers · 55 citations · 12 models
39 answers · 39 citations · 12 models
vendor site · LiveRamp33 answers · 39 citations · 11 models
vendor site · Guideflow29 answers · 29 citations · 9 models
24 answers · 30 citations · 11 models
vendor site · Funnel23 answers · 23 citations · 9 models
vendor site · Gartner20 answers · 22 citations · 11 models
20 answers · 20 citations · 9 models
vendor site · Amazon Web Services19 answers · 25 citations · 10 models
vendor site · SourceForge19 answers · 23 citations · 12 models
18 answers · 18 citations · 10 models
vendor site · Snowflake16 answers · 24 citations · 8 models
Pages the answers cite
The ten pages named in the most answers, by full address. A page here is one the models returned with a recommendation, not one the index endorses.
39 answers · 12 models
39 answers · 12 models
29 answers · 9 models
26 answers · 10 models
23 answers · 9 models
19 answers · 11 models
18 answers · 10 models
14 answers · 8 models
13 answers · 6 models
13 answers · 7 models
Search against answers
Each company's standing in the answers beside its site's footprint in Google search, one row a site: the products the models named on it with their shares, and the share they add up to; monthly searches on Google, and DataForSEO's estimate of AI search demand (modeled from search signals, directional, not a count of queries to any assistant), for the most-searched of the company's and its products' names (the name is in each row's hover text); estimated monthly organic visits to the site; and its best position in Google's top ten for “best data clean room”, “data clean room”. US estimates from DataForSEO and Google's Ads Transparency Center. A small company's site, or a mid-sized company's site for its flagship, is marked company; a product on a large parent's site (Google, Microsoft) has no site figures. A column with no figures for this category is left out, and an empty cell means none were seen, not none exist. Two measurements side by side: neither is read as the cause of the other.
| Company and products | Share | Own site cited | Name searches, Google | AI search demand, est. | Organic visits | Paid search a month, est. | Google ads, last 30 days | Best Google position |
|---|---|---|---|---|---|---|---|---|
| Snowflake Data Cloud snowflake.com Snowflake Data Clean Rooms 19% | 19% | 152 | 390 | 11 | 718,749 company | 118 | 6 | |
| AWS Clean Rooms | 15% | 720 | 4 | |||||
| Amazon parent site Amazon Marketing Cloud 14% | 14% | 60 | 151,000,000 | 1,380,939 | ||||
| Google parent site Google Ads Data Hub 10%, Google Cloud BigQuery Data Clean Rooms 2% | 12% | 69 | 140 | 0 | ||||
| InfoSum infosum.com | 10% | 114 | 390 | 7 | 362 | 5 | 6 | |
| Optable | 5% | 390 | 16 | |||||
| Decentriq decentriq.com | 3% | 86 | 170 | 1 | 911 | 2 | ||
| Crossbeam crossbeam.com | 3% | 46 | 5,400 | 97 | 4,256 | 3 | ||
| Placino | 3% | |||||||
| LiveRamp liveramp.com LiveRamp Clean Room 2%, LiveRamp Safe Haven 2% | 3% | 109 | 18,100 | 358 | 20,494 company | $339 | 44 | 4 |
Google's top ten for the two searches hold 16 sites; 3 of them are among the sites the models cited here (decentriq.com, gartner.com, liveramp.com). The first result for “best data clean room” is gartner.com.
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.ShowHide
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.
ShowHideModelDirect“What is the best data clean room for a mid-market B2B company?”Paraphrase“Which privacy-safe data collaboration platform would you recommend to a mid-sized B2B company?”Comparative“What are the top data clean rooms and how do they differ?”Budget-constrained“What is the best data clean room for a company with a limited budget?”Scale-constrained“We are a 500 person company evaluating a data clean room. What should we look at?”Negative“Which data clean rooms should I avoid or be cautious about?”
Claude Opus 5no first choiceno first choiceno first choiceno first choiceno first choicenothing named
Claude Opus 4.8no first choiceno first choiceno first choiceno first choiceno first choicenothing named
GPT-6 Astrano first choiceno first choiceno first choiceno first choiceno first choicenothing named
GPT-5.6 Solno first choiceno first choiceno first choiceno first choiceno first choicenothing named
Gemini 3.1 Prono first choiceno first choiceno first choiceno first choiceno first choicenothing named
Perplexity Sonar Prono first choiceno first choiceno first choiceno first choiceno first choicenothing named
Bold is the first choiceAlternatives are counted; the count opens them.What the answer argued against
The record
One row per call: the version string exactly as returned, whether the model searched, sources cited, and latency. Full answer text is in the free responses file. Download the record
Zero rows: every prompt, every model, every answer.
| Prompt | Model | Version string | Time (UTC) | Searched | Sources | Latency |
|---|
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
ShowHide
Category-scoped readings
Databricks read as Databricks Clean Rooms
LiveRamp read as LiveRamp Clean Room
LiveRamp (Data Collaboration Platform) read as LiveRamp Clean Room
LiveRamp (Habu) read as LiveRamp Clean Room
LiveRamp (incl. Habu acquisition) read as LiveRamp Clean Room
Meta read as Meta Advanced Analytics
Meta (Partnership Clean Room) read as Meta Advanced Analytics
Snowflake read as Snowflake Data Clean Rooms
Snowflake (Clean Rooms) read as Snowflake Data Clean Rooms
Snowflake Clean Rooms read as Snowflake Data Clean Rooms
Snowflake Data Clean Room read as Snowflake Data Clean Rooms
Unresolved, counted raw
ADH+
Adobe
Amazon PSA
Amazon Web Services Clean Rooms
AppsFlyer Clean Room
DataStax
Databricks clean room offerings
Datavant
Deciq
Dromo
Duality Technologies
Google
Google Ads measurement
Google BigQuery's clean room
Google Cloud (BigQuery Data Clean Rooms / Ads Data Hub)
Google Cloud (BigQuery Data Clean Rooms)
Google Cloud / BigQuery
Habanero Learning
IBM Watsonx.governance
LiveRamp Data Collaboration Platform (formerly Habu)
LiveRamp Data Collaboration Platform powered by Habu
LiveRamp Relate
MC2 Platform
Meta Advantage+ Audience Solutions
Meta’s PET-based collaborations
Microsoft
Microsoft Azure
Microsoft Azure Data Clean Room
Optable Collaborate
Oracle Clean Room
Salesforce
Salesforce Data Cloud Clean Rooms
Salesforce Data Cloud DCR
SecureScale
Snowflake DCR
Snowflake Secure Data Sharing
Snowflake’s Legacy Provider and Consumer Clean Rooms
Syseverse
Targeto
Thales
The Trade Desk's Galileo
TikTok Clean Room
Venn.cloud
Discontinued, still offered
No shut-down product was recommended here.