# Google BigQuery vs Amazon Redshift: which do AI models recommend for data warehouses, October 2026

IT AI Recommendation Index, October 2026 Edition, Data warehouses. Three of fourteen models named Google BigQuery first on the direct prompt; zero named Amazon Redshift. Page: https://it-ai-index.com/it-data/data-warehouses/google-bigquery-vs-amazon-redshift/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| Google BigQuery | 47% | #2 of 8 | 16% | 80 | 14 of 14 |
| Amazon Redshift | 2% | #3 of 8 | 16% | 80 | 14 of 14 |

## The direct prompt, model by model

- Grok 4.1 Fast: google bigquery first (first choices: Google BigQuery) (alternatives: Amazon Redshift, Snowflake)
- DeepSeek V4 Flash: google bigquery first (first choices: Google BigQuery, Snowflake) (alternatives: Amazon Redshift)
- Kimi K2: google bigquery first (first choices: Google BigQuery) (alternatives: Amazon Redshift, Snowflake)
- Claude Haiku 4.5: neither first, one named (first choices: Snowflake) (alternatives: Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQuery)
- GPT-5.4 mini: neither first, one named (first choices: Snowflake) (alternatives: Amazon Redshift, Google BigQuery, Microsoft Fabric Data Warehouse)
- Gemini 3.5 Flash: neither first, one named (first choices: Snowflake) (alternatives: Amazon Redshift, Google BigQuery, Microsoft Fabric Data Warehouse, MotherDuck)
- Perplexity Sonar: neither first, one named (first choices: Snowflake) (alternatives: Azure SQL Database, Google BigQuery, Microsoft Fabric Data Warehouse)
- Mistral Small: neither first, one named (first choices: Snowflake) (alternatives: Amazon Redshift, Google BigQuery, Microsoft Fabric Data Warehouse)
- Qwen 3.7 Flash: neither first, one named (first choices: Snowflake) (alternatives: Amazon Redshift, Databricks SQL, Google BigQuery)
- GLM 4.7 FlashX: neither first, one named (first choices: Snowflake) (alternatives: Amazon Redshift, Google BigQuery)
- MiniMax M2.5: neither first, one named (first choices: Snowflake) (alternatives: Amazon Redshift, Google BigQuery)
- GPT-6 Luna: neither first, one named (first choices: Snowflake) (alternatives: Amazon Redshift, Databricks SQL, Google BigQuery)
- Muse Glimmer 30B: neither first, one named (first choices: Snowflake) (alternatives: Amazon Redshift, Azure SQL Database, Google BigQuery)
- Llama 4 Maverick: neither named

## What the models said about Google BigQuery

- "On-demand charges are based on data processed... configure controls—or compare capacity pricing—before opening it up to lots of users." (GPT-6 Luna, negative prompt, soft negative)
- "Exercise Caution on Billing Surprises... harder for engineers to predict exactly what a specific query will cost" (Qwen 3.7 Flash, negative prompt, soft negative)
- "BigQuery is frequently cited as particularly risky for novices—people have reported massive unexpected bills" (MiniMax M2.5, negative prompt, soft negative)
- "Choose Google BigQuery if: Your workloads are unpredictable, you want to avoid "idle" costs, and you want safety against accidental massive bills." (Qwen 3.7 Flash, budget prompt, first choice)
- "BigQuery is the most popular choice for budget-conscious companies because it requires zero server management and has a generous free tier." (Gemini 3.5 Flash, budget prompt, first choice)
- "Snowflake if you have the budget and want to scale smoothly, or BigQuery if cost efficiency and serverless simplicity matter most" (Kimi K2, paraphrase prompt, first choice)

## What the models said about Amazon Redshift

- "Why avoid it: In a provisioned Redshift environment, you pay for the nodes 24/7 regardless of whether you are querying them." (Gemini 3.5 Flash, negative prompt, hard negative)
- "Most frequent cautions: Highest complexity for optimization/maintenance... Avoid if: Non-AWS shop, small team, or need serverless ease." (Grok 4.1 Fast, negative prompt, soft negative)
- "single-cloud options such as BigQuery on GCP and Redshift on AWS, are the ones practitioners most often advise to evaluate carefully" (Muse Glimmer 30B, negative prompt, soft negative)
- "Google BigQuery and Amazon Redshift are typically the most budget-friendly options" (Qwen 3.7 Flash, budget prompt, first choice)
- "If you are AWS-native with steady, high-concurrency reporting workloads, Redshift / Redshift Serverless gives predictable provisioned throughput." (Muse Glimmer 30B, paraphrase prompt, alternative)
- "Amazon Redshift Serverless has closed the gap significantly, but historically, traditional Redshift required more hands-on optimization." (Gemini 3.5 Flash, scale prompt, alternative)

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. 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.