Small business▲+16Since September 2026: 12% → 28%, +16 points. Past the 11-point floor: movement. Read over the models both editions asked.
28%from 12% in September 2026
Cleared the floor by 5 pointsRank 2 of 46, unchanged
8 categories · RankedSnowflake
265Judge labels
69First choices
67Negative labels
14 / 14Models named it
8Categories
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10.8, every buyer segment counted.
Best standing
62% in Data warehouses for enterprise buyers
Rank 1 of 26 in the mid-market standingendorsed leader
11 of 14 models made it the first choice on the direct prompt; 22% of its 78 labels there were negative.
What the models named instead of Snowflake →By buyer segmentStrongest at enterprise.
Small business2 of 49
24%73 labels
criticized challenger
Mid-market1 of 26
49%78 labels
endorsed leader
Enterprise1 of 42
62%75 labels
endorsed leader
In data warehouses · 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 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 warehouses | Data platform | 49% | 1 of 26 | 22% | 78 | endorsed leader | ▲+1Since September 2026: 47% → 48%, +1 point. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Data masking and test data management | Data platform | 0% | 137 of 140 | 50% | 4 | under 10 labels · led by DATPROF at 17% | |
| ETL and ELT | Data platform | 0% | 20 of 75 | 0% | 4 | under 10 labels · led by Fivetran at 40% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Data catalogs and governance | Data platform | 0% | 60 of 83 | 0% | 1 | under 10 labels · led by Atlan at 44% | |
| Data virtualization | Data platform | 0% | 44 of 99 | 0% | 1 | under 10 labels · led by Denodo at 28% | |
| Enterprise storage systems | Cloud and infrastructure | 0% | 160 of 167 | 100% | 1 | under 10 labels · led by Dell PowerStore at 16% | |
| Telemetry pipelines | IT operations and endpoint | 0% | 73 of 124 | 0% | 1 | under 10 labels · led by OpenTelemetry Collector at 37% | |
| Time series databases | Data platform | 0% | 31 of 66 | 0% | 1 | under 10 labels · led by TimescaleDB at 63% |
Movement
Since September 2026, Snowflake held within the floor in all eight categories: no change cleared 11 points.
Best category · Data warehouses · by segment
Mid-market▲+1Since September 2026: 47% → 48%, +1 point. Inside the 11-point floor: within noise. Read over the models both editions asked.
48%from 47% in September 2026
Inside the floor by 10 pointsRank 1 → 2 of 25
Enterprise▼−10Since September 2026: 72% → 62%, −10 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
62%from 72% in September 2026
Inside the floor by 1 pointRank 1 of 37, unchanged
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Data warehouses | 47% | 48% | ▲+1Since September 2026: 47% → 48%, +1 point. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 1 of 26, unchanged |
| Data masking | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 137 of 140, unchanged |
| ETL | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 21 → 20 of 75 |
| Data catalogs | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 60 of 83, unchanged |
| Data virtualization | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 44 of 99, unchanged |
| Enterprise storage | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 160 of 167, unchanged |
| Telemetry pipelines | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 73 of 124, unchanged |
| Time series DBs | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 31 of 66, 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 Snowflake across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.ShowHide
By model
How each model treated Snowflake across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
ShowHide| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 2 | 0 | 2 | 1 | 5 |
| GPT-5.4 mini | 3 | 3 | 2 | 0 | 8 |
| Gemini 3.5 Flash | 3 | 0 | 3 | 3 | 9 |
| Perplexity Sonar | 3 | 0 | 1 | 1 | 5 |
| Grok 4.20 | 1 | 2 | 1 | 2 | 6 |
| Mistral Small | 2 | 0 | 2 | 1 | 5 |
| DeepSeek V4 Flash | 2 | 3 | 0 | 2 | 7 |
| Llama 4 Maverick | 0 | 0 | 6 | 0 | 6 |
| Qwen 3.7 Flash | 1 | 2 | 4 | 2 | 9 |
| Kimi K2 | 3 | 1 | 0 | 2 | 6 |
| GLM 4.7 FlashX | 1 | 3 | 2 | 0 | 6 |
| MiniMax M2.5 | 2 | 1 | 2 | 3 | 8 |
| GPT-6 Luna | 2 | 1 | 1 | 1 | 5 |
| Muse Glimmer 30B | 4 | 0 | 0 | 2 | 6 |
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
Direct45 labels30
Paraphrase49 labels25
Comparative42 labels11not counted in share
Budget-constrained36 labels2
Scale-constrained43 labels12
Negative50 labels2not counted in share
First choiceAlternativeMentionNegative265 labels in all, every segment counted; 69 of the 82 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.
“For a typical mid-sized B2B company, I'd recommend Snowflake because: 1. It provides the best balance of features, scalability, and flexibility” MiniMax M2.5 · Data warehouses · paraphrase prompt · first choice
“If your team wants a platform that "just works" with almost zero database administration (DBA) overhead, Snowflake is the top recommendation.” Gemini 3.5 Flash · Data warehouses · paraphrase prompt · first choice
“"Snowflake offers balance. Stable, reliable, and scalable, and with smart engine sizing and auto-suspend, it can be cost-effective too."” Muse Glimmer 30B · Data warehouses · comparative prompt · first choice
“For many mid-market B2B companies, Snowflake is a popular choice due to its balance of ease of use, scalability, and flexibility.” Claude Haiku 4.5 · Data warehouses · direct 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.
“A securities lawsuit was filed against Snowflake alleging the company failed to disclose shortcomings in customer data security arrangements that allowed data breaches.” MiniMax M2.5 · Enterprise storage · negative prompt · hard negative
“What to Avoid on a Tight Budget - Snowflake: ... It's typically the most expensive option.” DeepSeek V4 Flash · Data warehouses · budget prompt · hard negative
“Avoid Snowflake on a tight budget.” Muse Glimmer 30B · Data warehouses · budget prompt · hard negative
“Many major database engines (e.g., SQL Server, Oracle, Snowflake) offer native, built-in Dynamic Data Masking (DDM) out of the box. While convenient, relying on these as your primary defense is highly risky.” Gemini 3.5 Flash · Data masking · negative prompt · soft negative
Named alongside
The products named in the same answers as Snowflake, over the 265 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Snowflake was named but was not.ShowHide
Named alongside
The products named in the same answers as Snowflake, over the 265 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Snowflake was named but was not.
ShowHideProductSame answerTook the first choice insteadHead to head
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. 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 228 of the 265 answers that named Snowflake and are not a share of its labels.
Domains cited
ovaledge.com124
clickhouse.com103
fortegrp.com102
fivetran.com84
atlan.com68
motherduck.com65
airbyte.com52
double.cloud46
scnsoft.com44
domo.com40
728 of the 728 domain citations in answers naming Snowflake came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Search and answers
Where Snowflake stands in Google search beside where it stands in the models' answers.ShowHide
Search and answers
Where Snowflake stands in Google search beside where it stands in the models' answers.
ShowHideIn search
Google, US estimatesPosition for “cloud data warehouse”
–
not in the top ten
Position for “cloud data warehouses”
–
not in the top ten
- Searches for its name, Google
- 368,000 a month (“snowflake”)
- AI search demand for its name, est.
- 37,077 a month
- 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)
In answers
This editionShare of first choices
49%
rank 1 of 26 in data warehouses
First choices
69
across its categories
- Named in
- 265 answers
- Its own site cited
- in 228 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
ShowHide
What it publishes
ShowHideAddresses on snowflake.com
11,795
subdomains included
Content
4,358
counted in the table below
Documentation
146
Product · Integration
145 · 1,508
| Kind | Pages | Last 90 days | 2025-10 to 2026-09 | Latest | Categories named |
|---|---|---|---|---|---|
| Blog | 1,589 | 7 | 2026-09-28 | ||
| Report or ebook | 900 | undated | |||
| Webinar or virtual event | 633 | 1 | 2026-09-11 | ||
| Case study | 386 | undated | |||
| Podcast or video | 315 | undated | |||
| News or press | 242 | undated | |||
| Conference or event | 139 | 9 | 2026-10-27 | ||
| Glossary or explainer | 131 | 0 | 2026-04-02 | ||
| Comparison | 18 | 1 | 2026-09-03 | ||
| Template or tool | 5 | 0 | 2025-12-09 |
Most recent
- 2026-10-27Rotterdam conference or event
- 2026-10-15New York City conference or event
- 2026-09-30London conference or event
- 2026-09-29Toronto conference or event
- 2026-09-29Berlin conference or event
- 2026-09-28Scaling mission ai lessons public sector blog
Events in person
Upcoming
- November 5, 2026Snowflake Forum ZurichThe Circle Convention Center Zurich Airport, Zürich, Switzerland · hosts
Last twelve months
- October 22, 2026Snowflake Forum MadridKinépolis (Pozuelo), Madrid, Spain · hosted
As the event pages on snowflake.com state them, read September 28, 2026.
How it is countedHide how it is counted
Every page snowflake.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 Snowflake
What the judge wrote, as written, with how often. The vendor table decides that these count as Snowflake; a claim can dispute any of them.
Snowflake (External Tables) 1Snowflake / Oracle Native Masking 1
Follow Snowflake
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 is its own company.ShowHide
The company
Snowflake is its own company.
ShowHideIn its own words
Stated by the vendor, not checked- Positioning
- The Snowflake AI Data Cloud - Mobilize Data, Apps, and AI
- For
- organizations
- Price stated
- Discover Snowflake pricing editions tailored to your security and compliance needs. Discover how you only pay for the storage and compute resources you use. snowflake.com/pricing
- Free plan or trial
- start for free snowflake.com
- Customers named
- Under ArmourNovo NordiskUnited RentalsBooking.comFanaticsAT&TCanvaPenske
- Not stated on the pages read
- Starting price, integrations, certifications, hosting
What Snowflake's own pages state, read September 28, 2026: snowflake.com, snowflake.com/pricing, trust.snowflake.com, snowflake.com/en/product, snowflake.com/en/customers. 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 Snowflake'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, 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 by email, built from the raw record of the edition. It shows:
- where Snowflake 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, 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 Snowflake is ranked in a category's top three this edition. Three sizes, one file each, light and dark; the code is under each.ShowHide
Badges
Wins only: a badge exists where Snowflake is ranked in a category's top three this edition. Three sizes, one file each, light and dark; the code is under each.
ShowHideAI models recommend Snowflake first in Data warehouses 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
Square · 240 × 240 LinkedIn, slides
Compact · 200 × 56 Email signature, footer
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.