Seven of fourteen models named BigQuery first on the direct prompt; zero named RudderStack Reverse ETL. Both were named by all fourteen models and BigQuery carries 75 labels and RudderStack Reverse ETL 52, so the shares are not directly comparable.
By Google, Mountain View, California, United States, founded 1998. Named in five categories this edition.
Named in one category 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 November 2026 Edition, BigQuery and RudderStack Reverse ETL were named in the same answer 120 times, of the 245 answers naming BigQuery and the 139 naming RudderStack Reverse ETL. In those answers RudderStack Reverse ETL took the first choice two times and BigQuery sixty-three.
| 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. 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
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“SQL- or configuration-heavy interfaces may require ongoing data-team support rather than allowing marketers to create and manage audiences independently” Perplexity Sonar · negative prompt · soft negative
“The platform is overkill for batch-only use cases, and marketing teams without engineering support will struggle to maintain the platform” Claude Haiku 4.5 · negative prompt · soft negative
“Requires strong data engineering expertise to maintain | More complex implementation than managed solutions” MiniMax M2.5 · negative prompt · soft negative
“using a reverse ETL tool such as Hightouch, Census, or RudderStack” Llama 4 Maverick · paraphrase prompt · first choice
“RudderStack is a popular choice for reverse ETL” Llama 4 Maverick · scale prompt · first choice
“Better if you need real-time event streaming + reverse ETL in one platform, but requires more engineering involvement” DeepSeek V4 Flash · paraphrase prompt · alternative
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.