# BigQuery vs Polytomic: which do AI models recommend for Warehouse & ETL, September 2026

GTM AI Recommendation Index, September 2026 Edition, Data warehouse and reverse ETL for marketing. Six of twelve models named BigQuery first on the direct prompt; one named Polytomic. Page: https://gtm-ai-index.com/gtm-data/data-warehouse-reverse-etl/bigquery-vs-polytomic/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| BigQuery | 24% | #2 of 14 | 11% | 65 | 12 of 12 |
| Polytomic | 1% | #6 of 14 | 14% | 21 | 9 of 12 |

## The direct prompt, model by model

- Claude Haiku 4.5: both first (first choices: BigQuery, Hightouch, Polytomic, Snowflake) (alternatives: Amazon Redshift, Hevo, RudderStack)
- Gemini 3.5 Flash: bigquery first (first choices: BigQuery, Hightouch, Snowflake) (alternatives: Census, Fivetran, dbt)
- Perplexity Sonar: bigquery first (first choices: BigQuery, Hightouch) (alternatives: Cometly, Fivetran, Funnel, Improvado, LeadJourney, Segment)
- Grok 4.1 Fast: bigquery first (first choices: BigQuery, Hightouch) (alternatives: Census, Snowflake)
- Mistral Small: bigquery first (first choices: BigQuery, Hightouch) (alternatives: Airbyte, Census, Databricks, Fivetran, Improvado, Snowflake, dbt)
- DeepSeek V4 Flash: bigquery first (first choices: BigQuery, Hightouch) (alternatives: Airbyte, Census, Fivetran, PostgreSQL, Snowflake, dbt)
- GPT-5.4 mini: neither first, one named (first choices: Hightouch, Snowflake) (alternatives: BigQuery, Census, Databricks, Fivetran, dbt)
- Qwen 3.7 Flash: neither first, one named (first choices: Hightouch, Snowflake) (alternatives: BigQuery, Census, Fivetran, Improvado, Polytomic, dbt)
- Kimi K2: neither first, one named (first choices: Hightouch, Snowflake) (alternatives: Airbyte, BigQuery, Census, Fivetran, Hevo, Improvado, Polytomic, dbt)
- GLM 4.7 FlashX: neither first, one named (first choices: Hightouch, Snowflake) (alternatives: BigQuery, Census, Databricks, Polytomic, dbt)
- MiniMax M2.5: neither first, one named (first choices: Hightouch, Snowflake) (alternatives: BigQuery, Census)
- Llama 4 Maverick: neither named

## What the models said about BigQuery

- "BigQuery (Proceed with Query Guardrails) ... can cost the company hundreds of dollars in a single click" (Gemini 3.5 Flash, negative prompt, soft negative)
- "BigQuery's pay-per-query model offers flexibility but can get unpredictable based on query volume." (Claude Haiku 4.5, negative prompt, soft negative)
- "unpredictable on-demand query costs ($6.25/TB scanned) spike on unoptimized marketing queries" (Grok 4.1 Fast, negative prompt, soft negative)
- "Google BigQuery | Best price-to-performance ratio; separates storage from compute so you only pay for what you query. Zero maintenance." (Qwen 3.7 Flash, paraphrase prompt, first choice)
- "For most mid-market companies, BigQuery's serverless model and lower operational overhead make it the easier starting point." (GLM 4.7 FlashX, paraphrase prompt, first choice)
- "BigQuery (free tier) → dlt or open-source Airbyte → dbt Core → Looker Studio, plus Adapters (~$49/month) for reverse ETL" (DeepSeek V4 Flash, budget prompt, first choice)

## What the models said about Polytomic

- "❌ Polytomic: Starts at $500/month" (GLM 4.7 FlashX, budget prompt, hard negative)
- "Be cautious if you need scale or marketing autonomy. - Limited destination coverage" (Kimi K2, negative prompt, soft negative)
- "While mentioned as an option, it's newer with limited market validation" (Mistral Small, negative prompt, soft negative)
- "Start with Hightouch or Polytomic" (Claude Haiku 4.5, direct prompt, first choice)
- "Best for: Small/mid-market teams needing bidirectional sync ... Notable caveat: Smaller destination library" (DeepSeek V4 Flash, comparative prompt, alternative)
- "Polytomic is often chosen by startups and mid-sized businesses with limited engineering bandwidth." (Claude Haiku 4.5, paraphrase prompt, alternative)

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve models, for a mid-market B2B company; rank is within the category. Comparisons are drawn for the top eight products in each category. Published under CC BY 4.0; the output is the models' output, and nothing here is a recommendation by the index.