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Data clean rooms · November 2026 Edition
Google Ads Data Hub vs Databricks Clean Rooms
One of fourteen models named Google Ads Data Hub first on the direct prompt; one named Databricks Clean Rooms. Google Ads Data Hub was named by fourteen of the fourteen models and Databricks Clean Rooms by thirteen and Google Ads Data Hub carries 43 labels and Databricks Clean Rooms 26, so the shares are not directly comparable.
Google Ads Data Hub
accepted challengerBy Google, Mountain View, California, United States, founded 1998. Named in one category this edition.
By Databricks, San Francisco, United States, founded 2013. Named in one category this edition.
First-choice share15%3%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate21%12%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#6A position in a field of 11; printed, not drawn.
Labels4326A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Google Ads Data Hub reading right to left. Rank and label count are printed, not drawn.Snowflake Data Clean Rooms was named alongside these two in thirteen of the fourteen direct answers. Snowflake Data Clean Rooms vs Google Ads Data Hub · Snowflake Data Clean Rooms vs Databricks Clean Rooms · Amazon Marketing Cloud vs Google Ads Data Hub
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the data clean rooms page.
By framing
How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
Google Ads Data HubFirst choices, of fourteen modelsDatabricks Clean Rooms
Direct111 against Google Ads Data Hub · 1 against Databricks Clean Rooms
Paraphrase012 against Google Ads Data Hub · 1 against Databricks Clean Rooms
Comparative00
Budget-constrained901 against Databricks Clean Rooms
Scale-constrained001 against Google Ads Data Hub
Negative015 against Google Ads Data Hub
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.
Across every category in the November 2026 Edition, Google Ads Data Hub and Databricks Clean Rooms were named in the same answer thirty-nine times, of the 101 answers naming Google Ads Data Hub and the 74 naming Databricks Clean Rooms. In those answers Databricks Clean Rooms took the first choice one time and Google Ads Data Hub two.
Every model, every framing
The eighty-four answers behind the chart above, one cell each: where Google Ads Data Hub and Databricks Clean Rooms stood in it.
| Model | DirectGA | ParaphraseGA | ComparativeGA | Budget-constrainedGA | Scale-constrainedGA | NegativeGA |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | GA | GA | GA | |||
| GPT-5.4 mini | GA | | ||||
| Gemini 3.5 Flash | | GA | GA | | GA | |
| Perplexity Sonar | GA | GA | GA | |||
| Grok 4.20 | | GA | GA | GA | GA | |
| Mistral Small | GA | GA | ||||
| DeepSeek V4 Flash | GA | GA | GA | GA | GA | GA |
| Llama 4 Maverick | GA | GA | GA | |||
| Qwen 3.7 Flash | GA | |||||
| Kimi K2 | GA | GA | GA | |||
| GLM 4.7 FlashX | GA | GA | ||||
| MiniMax M2.5 | GA | |||||
| GPT-6 Luna | | | GA | |||
| Muse Glimmer 30B | | GA | GA |
GA Google Ads Data Hub Databricks Clean RoomsGA first choiceGA named as an alternativeGA argued againstblank: not namedEach cell is one answer, Google Ads Data Hub on the left and Databricks Clean Rooms on the right.
Databricks Clean RoomsGA first choiceGA named as an alternativeGA argued againstblank: not namedEach cell is one answer, Google Ads Data Hub on the left and Databricks Clean Rooms on the right.The direct prompt
The plain question, one answer per model, grouped by where Google Ads Data Hub and Databricks Clean Rooms stood in it.
Google Ads Data Hub first, Databricks Clean Rooms not the choice
1 of 14 modelsDatabricks Clean Rooms was named in the answer but not as the choice, or not at all.Llama 4 MaverickGoogle Ads Data Hub alternatives: AWS Clean Rooms, Amazon Marketing Cloud, Meta Advanced Analytics, Snowflake Data Clean Rooms
Databricks Clean Rooms first, Google Ads Data Hub not the choice
1 of 14 modelsGoogle Ads Data Hub was named in the answer but not as the choice, or not at all.Gemini 3.5 FlashDatabricks Clean Rooms, Snowflake Data Clean Rooms alternatives: Google BigQuery Data Clean Rooms, Habu, InfoSum
Neither was the first choice, one was named
6 of 14 modelsThe answer put something else first and named one of the two as an alternative.Claude Haiku 4.5AWS Clean Rooms, Snowflake Data Clean Rooms alternatives: Amazon Marketing Cloud, Google Ads Data Hub
Perplexity SonarSnowflake Data Clean Rooms alternatives: AWS Clean Rooms, Databricks Clean Rooms, LiveRamp Clean Room
DeepSeek V4 FlashSnowflake Data Clean Rooms alternatives: AWS Clean Rooms, Amazon Marketing Cloud, Crossbeam, Google Ads Data Hub, LiveRamp Clean Room
Kimi K2AWS Clean Rooms, Snowflake Data Clean Rooms alternatives: Amazon Marketing Cloud, Crossbeam, Google Ads Data Hub, InfoSum
GLM 4.7 FlashXCrossbeam alternatives: Google Ads Data Hub, Snowflake Data Clean Rooms
GPT-6 LunaSnowflake Data Clean Rooms alternatives: AWS Clean Rooms, Databricks Clean Rooms
Neither was named
6 of 14 modelsThe answer made no first choice from these two in this category.GPT-5.4 miniSnowflake Data Clean Rooms alternatives: AWS Clean Rooms
Grok 4.20Snowflake Data Clean Rooms alternatives: AWS Clean Rooms, Amazon Marketing Cloud, Google Cloud BigQuery or Ads Data Hub, LiveRamp Clean Room
Mistral SmallSnowflake Data Clean Rooms alternatives: AWS Clean Rooms, LiveRamp Clean Room
Qwen 3.7 FlashGravic Clean Room, InfoSum, Snowflake Data Exchange / Partner Extensions alternatives: Salesforce Identity Resolution
MiniMax M2.5LiveRamp Safe Haven, Snowflake Data Clean Rooms alternatives: AWS Clean Rooms, InfoSum
Muse Glimmer 30BSnowflake Data Clean Rooms alternatives: AWS Clean Rooms, InfoSum, LiveRamp Safe Haven
Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.
By buyer segment
The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Google Ads Data Hub leads by eleven points.
Google Ads Data Hub11%#3 of 13
Databricks Clean Rooms0%#13 of 13Mid-marketThe figures above
Google Ads Data Hub leads by twelve points.
Google Ads Data Hub15%#3 of 11
Databricks Clean Rooms3%#6 of 11Enterprise
The order flips: Databricks Clean Rooms leads at enterprise.
Databricks Clean Rooms6%#5 of 11Google Ads Data Hub0%#9 of 11
The full enterprise standing →What the models said about Google Ads Data Hub
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Walled garden clean rooms (Google Ads Data Hub, Amazon Marketing Cloud): These are *B2C advertising-focused* and not relevant for most B2B data collaboration use cases.” DeepSeek V4 Flash · paraphrase prompt · hard negative
“What to approach with caution: Native clean rooms operated by major media platforms (e.g., Google Ads Data Hub, Amazon Marketing Cloud, Meta Advanced Analytics)” Gemini 3.5 Flash · negative prompt · soft negative
“regulatory scrutiny (e.g., ongoing antitrust and privacy probes in the EU/US) means potential changes or restrictions. Risks include ecosystem bias” Grok 4.20 · negative prompt · soft negative
“Best all‑around for most advertisers: Google Ads Data Hub (if you're Google‑heavy) or Amazon Marketing Cloud (if you're Amazon‑heavy). Both are free and easy to set up.” GLM 4.7 FlashX · budget prompt · first choice
“The free walled-garden options are the realistic start... Google Ads Data Hub provides clean room analysis for advertisers running campaigns on Google properties.” Muse Glimmer 30B · budget prompt · first choice
“the best data clean rooms are the free or low-cost "walled-garden" options from major platforms. These include: - Google Ads Data Hub” Mistral Small · budget prompt · first choice
What the models said about Databricks Clean Rooms
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“Databricks requires data to live in Databricks storage or an accessible cloud bucket, which can add setup complexity” GPT-5.4 mini · budget prompt · soft negative
“Strong for advanced analytics if you're in that ecosystem, but steeper learning curve for mid-market teams.” Grok 4.20 · direct prompt · soft negative
“more accessible than heavy engineering-heavy options like raw Databricks or AWS Clean Rooms” Grok 4.20 · paraphrase prompt · soft negative
“Databricks Clean Rooms is generally the most flexible for mid-size companies needing cross-cloud, privacy-policy governed collaboration with full audit logs.” Muse Glimmer 30B · paraphrase prompt · first choice
“Prefer neutral, interoperable platforms (like Snowflake, Databricks, AWS Clean Rooms, InfoSum, or independent providers)” DeepSeek V4 Flash · negative prompt · first choice
“start with your primary Cloud Data Warehouse's native DCR (typically Snowflake DCR or Databricks Clean Rooms)” Gemini 3.5 Flash · direct prompt · first choice
Also compared
Snowflake Data Clean Rooms vs Google Ads Data HubSnowflake Data Clean Rooms vs Databricks Clean RoomsAmazon Marketing Cloud vs Google Ads Data HubAmazon Marketing Cloud vs Databricks Clean RoomsGoogle Ads Data Hub vs AWS Clean RoomsGoogle Ads Data Hub vs Meta Advanced AnalyticsGoogle Ads Data Hub vs InfoSumGoogle Ads Data Hub vs LiveRamp Clean RoomAWS Clean Rooms vs Databricks Clean RoomsMeta Advanced Analytics vs Databricks Clean RoomsDatabricks Clean Rooms vs InfoSumDatabricks Clean Rooms vs LiveRamp Clean RoomAll twenty-eight head-to-head pages and the full data clean rooms standing
Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.