BigQuery vs Snowflake
Seven of fourteen models named BigQuery first on the direct prompt; eight named Snowflake. Both were named by all fourteen models and BigQuery carries 75 labels and Snowflake 68, so the shares are not directly comparable.
By Google, Mountain View, California, United States, founded 1998. Named in five categories this edition.
By Snowflake Inc., San Mateo, United States, founded 2012. Named in four 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.
By framing
BigQueryFirst choices, of fourteen modelsSnowflake
Across every category in the November 2026 Edition, BigQuery and Snowflake were named in the same answer 216 times, of the 245 answers naming BigQuery and the 273 naming Snowflake. In those answers Snowflake took the first choice forty-seven times and BigQuery sixty-eight.
Every model, every framing
| 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 | | | |
BigQuery Snowflake first choice named as an alternative argued againstblank: not namedEach cell is one answer, BigQuery on the left and Snowflake on the right.The direct prompt
Both were the first choice
4 of 14 modelsThe answer named them together, and the judge labeled each a first choice.BigQuery first, Snowflake an alternative
3 of 14 modelsSnowflake was named in the answer but not as the choice, or not at all.Snowflake first, BigQuery an alternative
4 of 14 modelsBigQuery was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
2 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
1 of 14 modelsThe answer made no first choice from these two in this category.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
BigQuery44%#1 of 18Snowflake7%#3 of 18Snowflake32%#2 of 12BigQuery7%#4 of 12What the models said about BigQuery
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of five in this category shown.
“Using Snowflake, BigQuery, or Databricks directly for marketing activation... they offer zero native activation” Qwen 3.7 Flash · negative prompt · soft negative
“marketing teams should be careful if they need tight cost control and predictable execution at scale” GPT-5.4 mini · negative prompt · soft negative
“If your budget is lean and you rely heavily on GA4/Google Ads: Go with Google BigQuery (DW) + Hightouch or Census (Reverse ETL).” Gemini 3.5 Flash · comparative prompt · first choice
“Choose BigQuery if you're heavily invested in Google Marketing Platform (GA4, Google Ads) — the native exports make setup trivial” Kimi K2 · direct prompt · first choice
“Often the #1 choice for marketing teams because it natively connects to Google's marketing platforms without third-party ETL tools.” DeepSeek V4 Flash · comparative prompt · first choice
What the models said about Snowflake
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of six in this category shown.
“Snowflake, BigQuery, Redshift, Databricks are excellent for analytics but: Data is only accessible to technical SQL users” Kimi K2 · negative prompt · soft negative
“Using Snowflake, BigQuery, or Databricks directly for marketing activation... they offer zero native activation” Qwen 3.7 Flash · negative prompt · soft negative
“Cost and lock-in are the recurring complaints... often seen as one of the most expensive cloud data warehouses.” Muse Glimmer 30B · negative prompt · soft negative
“For most mid-sized B2B companies, Snowflake + Census + Segment + Fivetran + dbt is a robust, scalable, and maintainable stack.” Mistral Small · paraphrase prompt · first choice
“Choose Snowflake if you need multi-cloud flexibility or have broader organizational data needs beyond marketing” Kimi K2 · direct prompt · first choice
“What to use instead: Snowflake or Google BigQuery. Both offer serverless auto-scaling, low maintenance” Gemini 3.5 Flash · negative 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.