| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Data clean rooms | GTM data and infrastructure | 19% | 1 of 100 | 10% | 52 | accepted challenger |
| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 2 | 1 | 1 | 0 | 4 |
| GPT-5.4 mini | 1 | 3 | 1 | 0 | 5 |
| Gemini 3.5 Flash | 1 | 5 | 0 | 0 | 6 |
| Perplexity Sonar | 2 | 1 | 0 | 0 | 3 |
| Grok 4.1 Fast | 2 | 2 | 0 | 1 | 5 |
| Mistral Small | 0 | 1 | 1 | 0 | 2 |
| DeepSeek V4 Flash | 0 | 3 | 0 | 2 | 5 |
| Llama 4 Maverick | 0 | 0 | 2 | 0 | 2 |
| Qwen 3.7 Flash | 2 | 1 | 1 | 0 | 4 |
| Kimi K2 | 0 | 2 | 1 | 1 | 4 |
| GLM 4.7 FlashX | 2 | 1 | 1 | 0 | 4 |
| MiniMax M2.5 | 0 | 0 | 1 | 0 | 1 |
| GPT-6 Luna | 1 | 2 | 0 | 1 | 4 |
| Muse Glimmer 30B | 3 | 0 | 0 | 0 | 3 |
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
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
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.
489 of the 592 domain citations in answers naming Snowflake Data Clean Rooms came from somebody else's page.
Pages are listed as the models cited them.
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.
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.
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
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.
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:
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.
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.