Nine of fourteen models named Snowflake first on the direct prompt; two named Census. Both were named by all fourteen models and Snowflake carries 70 labels and Census 80, so the shares are not directly comparable.
By Snowflake Inc., San Mateo, United States, founded 2012. Named in three categories this edition.
By Fivetran, United States. Named in five categories this edition.
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 warehouse and reverse ETL for marketing page.
Across every category in the October 2026 Edition, Snowflake and Census were named in the same answer 179 times, of the 272 answers naming Snowflake and the 250 naming Census. In those answers Census took the first choice eleven times and Snowflake forty-eight.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | ||||||
| GPT-5.4 mini | ||||||
| Gemini 3.5 Flash | ||||||
| Perplexity Sonar | ||||||
| Grok 4.20 | ||||||
| Mistral Small | ||||||
| DeepSeek V4 Flash | ||||||
| Llama 4 Maverick | ||||||
| Qwen 3.7 Flash | ||||||
| Kimi K2 | ||||||
| GLM 4.7 FlashX | ||||||
| MiniMax M2.5 | ||||||
| GPT-6 Luna | ||||||
| Muse Glimmer 30B |
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.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“Avoid Snowflake and enterprise ETL tools” DeepSeek V4 Flash · budget prompt · hard negative
“General Purpose Warehouses: (e.g., Snowflake via partner templates) — More control, harder setup, higher engineering overhead.” Qwen 3.7 Flash · scale prompt · soft negative
“Snowflake lacks a permanent free tier (only 30-day trial), making it less ideal for long-term budget use.” MiniMax M2.5 · budget prompt · soft negative
“Snowflake + dbt Cloud + Hightouch is the most generally "best" marketing data warehouse + reverse ETL stack for a mid-market B2B company.” GPT-5.4 mini · direct prompt · first choice
“Snowflake is ideal for mid-sized B2B companies offering scalability, cross-cloud flexibility, and strong marketing platform integrations” MiniMax M2.5 · paraphrase prompt · first choice
“Snowflake is the most popular for mid-market B2B companies due to its ease of use, strong performance, and excellent integrations.” Mistral Small · paraphrase prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Don't rush into dedicated reverse ETL tools (especially Census post-acquisition)... this is the one I'd flag most strongly as "be cautious."” DeepSeek V4 Flash · negative prompt · hard negative
“Census assumes your data is already clean and modeled... You need a data engineering team or analytics engineer managing warehouse hygiene before Census delivers value.” Claude Haiku 4.5 · negative prompt · soft negative
“Pricing model shift: Moved from flat-fee to consumption-based Monthly Active Rows (MAR), making costs harder to predict” MiniMax M2.5 · negative prompt · soft negative
“compare Hightouch with Fivetran Activations (the current Fivetran product incorporating Census reverse-ETL capabilities)” GPT-6 Luna · scale prompt · first choice
“Both industry-leading Reverse ETL platforms offer a permanent free tier of 1 active destination with unlimited syncs/runs.” Gemini 3.5 Flash · budget prompt · first choice
“BigQuery + Fivetran + dbt + Census + Looker Studio is the strongest, most cost-effective combination” DeepSeek V4 Flash · direct prompt · first choice
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.