Every category where a model named BigQuery 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.

Category	Function	Share	Rank	Negative rate	Labels	Quadrant	Since September 2026
Data warehouse and reverse ETL for marketing	GTM data and infrastructure	21%	2 of 83	4%	73	accepted challenger	▼−2Since September 2026: 24% → 22%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
Web analytics	GTM data and infrastructure	3%	7 of 91	0%	4	under 10 labels · led by Google Analytics 4 at 57%
Data clean rooms	GTM data and infrastructure	2%	15 of 100	20%	5	under 10 labels · led by Snowflake Data Clean Rooms at 19%
Data management platforms	GTM data and infrastructure	0%	22 of 159	0%	10	accepted challenger	▼−5Since September 2026: 5% → 0%, −5 points. Inside the 11-point floor: within noise. Read over the models both editions asked.

Movement

Since September 2026, BigQuery held within the floor in all four categories: no change cleared 11 points.

Best category · Warehouse & ETL · by segment

Small business=heldSince September 2026: 35% → 35%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.

35%from 35% in September 2026

Inside the floor by 11 pointsRank 2 of 92, unchanged

Mid-market▼−2Since September 2026: 24% → 22%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.

22%from 24% in September 2026

Inside the floor by 9 pointsRank 2 of 81, unchanged

Enterprise▼−5Since September 2026: 11% → 6%, −5 points. Inside the 11-point floor: within noise. Read over the models both editions asked.

6%from 11% in September 2026

Inside the floor by 6 pointsRank 3 → 4 of 79

All categories · Mid-market

Category	September 2026	Now	Change	Reading	Rank
DMP	5%	0%	▼−5Since September 2026: 5% → 0%, −5 points. Inside the 11-point floor: within noise. Read over the models both editions asked.	Within noise	Rank 5 → 22 of 159
Web analytics	0%	4%	newNew since September 2026: not ranked then, 4% now.	New this edition	Rank 7 of 91, unchanged
Warehouse & ETL	24%	22%	▼−2Since September 2026: 24% → 22%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.	Within noise	Rank 2 of 83, unchanged
Data clean rooms	0%	2%	newNew since September 2026: not ranked then, 2% now.	New this edition	Rank 15 of 100, unchanged

Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.

The floor is 11 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. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions

By model

How each model treated BigQuery across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.

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Model	First choice	Alternative	Mention	Negative	Labels
Claude Haiku 4.5	0	2	1	0	3
GPT-5.4 mini	3	2	3	0	8
Gemini 3.5 Flash	3	4	0	0	7
Perplexity Sonar	1	3	1	0	5
Grok 4.1 Fast	5	2	1	0	8
Mistral Small	5	0	1	0	6
DeepSeek V4 Flash	2	4	1	2	9
Llama 4 Maverick	0	1	1	0	2
Qwen 3.7 Flash	1	4	1	0	6
Kimi K2	3	5	0	0	8
GLM 4.7 FlashX	1	5	1	0	7
MiniMax M2.5	5	1	1	0	7
GPT-6 Luna	1	2	3	1	7
Muse Glimmer 30B	2	4	2	1	9

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

Direct44 labels18

Paraphrase42 labels7

Comparative59 labels23not counted in share

Budget-constrained47 labels27

Scale-constrained37 labels17

Negative42 labels6not counted in share

First choiceAlternativeMentionNegative271 labels in all, every segment counted; 69 of the 98 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.

“the most practical stack is usually BigQuery + self-hosted Airbyte + dbt + Metabase, with BigQuery as the warehouse” Perplexity Sonar · Warehouse & ETL · budget prompt · first choice

“BigQuery is often the default choice for modern marketing teams because of its deep integration with the Google ecosystem.” Gemini 3.5 Flash · Warehouse & ETL · comparative prompt · first choice

“Most marketing teams today pair BigQuery (for Google ecosystem) or Snowflake (for multi-cloud flexibility)” MiniMax M2.5 · Warehouse & ETL · comparative prompt · first choice

“BigQuery offers an incredibly generous free tier: 10 GB of storage and 1 TB of query scanning per month.” Gemini 3.5 Flash · Warehouse & ETL · budget 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.

“I wouldn't automatically avoid BigQuery, Snowflake, or Redshift... BigQuery charges for query processing... careless or frequent queries can affect the bill” GPT-6 Luna · Warehouse & ETL · negative prompt · soft negative

“"BigQuery is built for speed and scale, but marketing teams often discover its limitations only after months of custom pipeline work. Query cost spirals."” Muse Glimmer 30B · Warehouse & ETL · negative prompt · soft negative

“Query cost explosions: Exploratory queries on 1TB+ tables without partition filters can cost $50–$200 per run” DeepSeek V4 Flash · Warehouse & ETL · negative prompt · soft negative

“Walled Garden Clean Rooms (Google, Meta, Amazon) ... Why to be cautious: Vendor lock-in” DeepSeek V4 Flash · Data clean rooms · negative prompt · soft negative

Named alongside

The products named in the same answers as BigQuery, over the 271 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and BigQuery was named but was not.

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ProductSame answerTook the first choice insteadHead to head

Snowflake235 of 27161Compare →

Hightouch213 of 27186Compare →

Census184 of 27121Compare →

Fivetran139 of 2711Not among the top eight

Amazon Redshift133 of 2710Not among the top eight

dbt102 of 2710Not among the top eight

Airbyte91 of 2711Compare →

RudderStack Reverse ETL84 of 2713Compare →

Databricks SQL Warehouse82 of 2710Not among the top eight

Segment53 of 2711Not 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 BigQuery. 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 248 of the 271 answers that named BigQuery and are not a share of its labels.

Domains cited

improvado.io152

guideflow.com103

hightouch.com102

leadjourney.io69

airbyte.com62

cdp.com60

supermetrics.com60

funnel.io59

portermetrics.com57

aboutmartech.com55

779 of the 779 domain citations in answers naming BigQuery came from somebody else's page.

Pages cited

guideflow.com/blog/reverse-etl-tools92

improvado.io/blog/best-reverse-etl-tools92

leadjourney.io/blog/best-marketing-data-warehouse68

supermetrics.com/blog/marketing-data-warehousing55

zoho.com/dataprep/top-reverse-etl-tools.html52

airbyte.com/top-etl-tools-for-sources/reverse-etl-tools51

aboutmartech.com/blog/reverse-etl-tools46

portermetrics.com/en/compare/7-best-marketing-data-warehouse-reporting-and-dashobards-tool43

Pages are listed as the models cited them.

Search and answers

cloud.google.com is not in Google's top ten for any of the category's searches. In the answers, BigQuery takes 21% of first choices and Hightouch takes 40%.

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In search

Google, US estimates

Position for “marketing data warehouse and reverse etl stack”

–

not in the top ten

Position for “best marketing data warehouse and reverse etl stack”

–

not in the top ten

Searches for its name, Google: 22,200 a month (“bigquery”)
AI search demand for its name, est.: 2,048 a month
Organic visits to its site: about 7,405,347 a month
Searches its site ranks for: 70,320 · 16,032 in the top three
Sites linking to it: 201,334
Paid Google search: No ads found in the estimate; that does not mean it runs none

Ads on Google

None found in Google's ad transparency records for the US

In answers

This edition

Share of first choices

21%

rank 2 of 83 in Warehouse & ETL

Segment leader

40%

Hightouch

First choices: 69 across its categories
Named in: 271 answers
Its own site cited: in 248 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.

What it publishes

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Addresses on cloud.google.com

subdomains included

Content

counted in the table below

Documentation

Product · Integration

0 · 0

Kind	Pages	Last 90 days	Latest
Blog	37	14	2026-09-28
Case study	19	undated
Conference or event	4	undated
Report or ebook	2	undated
Glossary or explainer	2	undated
Webinar or virtual event	1	undated
Template or tool	1	undated
News or press	1	undated

Most recent

2026-09-28Storage optimized z4d vm and bare metal instances blog
2026-09-28Accelerate geospatial coding with ai in google earth engine blog
2026-09-25Storage intelligence advisor and batch operations updates blog
2026-09-25Memorystore for valkey 9 1 3x qps caching blog
2026-09-252026 gartner magic quadrant for container management blog
2026-09-24Gemini 3 8 live with live avatar is now generally available blog

How it is countedHide how it is counted

Every page cloud.google.com exposes, subdomains included. Kind is read from the address and title. The last 90 days, the latest date and the twelve months count pages by when they were published, from the site's feeds, a date in the address, or the page's own publication date, read from up to a hundred of its most recently changed pages; a page that says only when it last changed is counted in its kind but not in when, so the recent counts are a floor, and a kind none of whose pages gives a publication date reads undated. An event counts as online when its address or title says so (webinar, on demand, virtual or online summit); a conference, summit, trade show, expo or roadshow that does not say so is counted as a conference or event, which on a vendor's site is mostly in person. Read September 29, 2026.

Names read as BigQuery

What the judge wrote, as written, with how often. The vendor table decides that these count as BigQuery; a claim can dispute any of them.

Google BigQuery 43Google Analytics 4 (GA4) + BigQuery 2Google Ads Data Hub / Google BigQuery 1

Follow BigQuery

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

Google is the company behind BigQuery.

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On record

Wikidata

Website: google.com
Headquarters: Mountain View, California, United States
Founded: 1998
Ownership: Part of Alphabet Inc.
Also from Google: Adometry, Attribution 360, Firebase, Google ADH, Google Ad Manager, Google AdMob, Google AdSense, Google Address Validation and 81 more

Fetched September 14, 2026, with a correction applied. These describe the company, not the product's standing, and a claimed page can dispute any of them. · Wikidata

In its own words

Stated by the vendor, not checked

Positioning: Autonomous data to AI platform for analytics and data science.
cloud.google.com
Price stated: BigQuery compared to cloud data warehouse alternatives cloud.google.com
Customers named: MLB
Not stated on the pages read: Who it is for, starting price, free plan or trial, integrations, certifications, hosting

What BigQuery's own pages state, read September 28, 2026: cloud.google.com. A claimed page can correct any of them.

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 BigQuery'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 BigQuery, 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 BigQuery by email, built from the raw record of the edition. It shows:

where BigQuery 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 BigQuery, 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.

Badges

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

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BigQuery is among the products AI models recommend first in Data warehouse and reverse ETL for marketing 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

Show the code

<a href="https://gtm-ai-index.com/gtm-data/data-warehouse-reverse-etl/"><img src="https://gtm-ai-index.com/badges/2026-10/bigquery--data-warehouse-reverse-etl-wide.svg" alt="Among AI models' top three in Data warehouse and reverse ETL for marketing, 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 warehouse and reverse ETL for marketing standing, where the claim can be checked.

Square · 240 × 240 LinkedIn, slides

Show the code

<a href="https://gtm-ai-index.com/gtm-data/data-warehouse-reverse-etl/"><img src="https://gtm-ai-index.com/badges/2026-10/bigquery--data-warehouse-reverse-etl-square.svg" alt="Among AI models' top three in Data warehouse and reverse ETL for marketing, 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 warehouse and reverse ETL for marketing standing, where the claim can be checked.

Compact · 200 × 56 Email signature, footer

Show the code

<a href="https://gtm-ai-index.com/gtm-data/data-warehouse-reverse-etl/"><img src="https://gtm-ai-index.com/badges/2026-10/bigquery--data-warehouse-reverse-etl-compact.svg" alt="Among AI models' top three in Data warehouse and reverse ETL for marketing, 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 warehouse and reverse ETL for marketing 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.