Data warehouses · September 2026 Edition
Google BigQuery vs ClickHouse Cloud
Three of twelve models named Google BigQuery first on the direct prompt; zero named ClickHouse Cloud. Google BigQuery was named by twelve of the twelve models and ClickHouse Cloud by eleven and Google BigQuery carries 67 labels and ClickHouse Cloud 22, so the shares are not directly comparable.
Named in two categories this edition.
Named in one category this edition.
First-choice share44%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate16%14%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#3A position in a field of 7; printed, not drawn.
Labels6722A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Google BigQuery reading right to left. Rank and label count are printed, not drawn.Snowflake was named alongside these two in eleven of the twelve direct answers. Snowflake vs Google BigQuery · Snowflake vs ClickHouse Cloud
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; every quote names the model and the prompt it came from. Both figures come from the data warehouses page.
By framing
How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
Google BigQueryFirst choices, of twelve modelsClickHouse Cloud
Direct301 against ClickHouse Cloud
Paraphrase30
Comparative40
Budget-constrained111
Scale-constrained30
Negative0011 against Google BigQuery · 2 against ClickHouse Cloud
Bars are first choices, 0 to 12 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to twelve.
The direct prompt
The plain question, one answer per model, grouped by where Google BigQuery and ClickHouse Cloud stood in it.
Google BigQuery first, ClickHouse Cloud not the choice
3 of 12 modelsClickHouse Cloud was named in the answer but not as the choice, or not at all.Mistral SmallGoogle BigQuery, Snowflake
Kimi K2Google BigQuery alternatives: Amazon Redshift, Snowflake
GLM 4.7 FlashXGoogle BigQuery alternatives: Amazon Redshift, Microsoft Fabric, Snowflake
Neither was the first choice, one was named
8 of 12 modelsThe answer put something else first and named one of the two as an alternative.GPT-5.4 miniSnowflake alternatives: Amazon Redshift, Databricks SQL, Google BigQuery
Gemini 3.5 FlashSnowflake alternatives: Amazon Redshift, Google BigQuery, Microsoft Fabric
Perplexity SonarSnowflake alternatives: Amazon Redshift, Azure SQL Database, Databricks, Google BigQuery, Microsoft Fabric
Grok 4.1 FastSnowflake alternatives: Amazon Redshift, Google BigQuery
DeepSeek V4 FlashSnowflake alternatives: Amazon Redshift, Google BigQuery
Llama 4 MaverickSnowflake alternatives: Azure SQL Database, Google BigQuery
Qwen 3.7 FlashSnowflake alternatives: Amazon Redshift, Google BigQuery, Microsoft Fabric
MiniMax M2.5Snowflake alternatives: Amazon Redshift, Azure Synapse Analytics, Databricks, Google BigQuery
Neither was named
1 of 12 modelsThe answer made no first choice from these two in this category.Claude Haiku 4.5no first choice alternatives: Firebolt
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
The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Google BigQuery leads by eighty points.
Google BigQuery80%#1 of 8ClickHouse Cloud0%#6 of 8Mid-marketThe figures above
Google BigQuery leads by forty-two points.
Google BigQuery44%#2 of 7ClickHouse Cloud2%#3 of 7Enterprise
Google BigQuery leads by thirteen points.
Google BigQuery13%#3 of 8ClickHouse Cloud0%#8 of 8What the models said about Google BigQuery
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“BigQuery can be great, but on-demand query pricing can surprise teams if you don't put quotas and guardrails in place.” GPT-5.4 mini · negative prompt · soft negative
“Pay-per-Query Volatility... To use BigQuery safely, you must enforce strict query cost limits” Gemini 3.5 Flash · negative prompt · soft negative
“BigQuery, which is not suitable for live data or situations that require frequent mutations.” Llama 4 Maverick · negative prompt · soft negative
“Features a generous free tier with 1TB of query data per month and 10GB of storage. It's highly cost-effective for sporadic queries and has no minimum commitment.” Claude Haiku 4.5 · budget prompt · first choice
“If cost is your primary concern: Choose BigQuery - it's significantly cheaper at mid-market scale and requires zero infrastructure management.” Kimi K2 · direct prompt · first choice
“Google BigQuery: A serverless, pay-as-you-go solution with a generous free tier, ideal for flexible, ad-hoc analytics, and startups.” Llama 4 Maverick · budget prompt · first choice
What the models said about ClickHouse Cloud
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“Less mature for multi‑tenant concurrency and BI tooling; requires more tuning” MiniMax M2.5 · direct prompt · soft negative
“more tuning and topology planning may be needed for strict SLAs” Perplexity Sonar · negative prompt · soft negative
“Caution with a Strong Condition: ClickHouse” DeepSeek V4 Flash · negative prompt · soft negative
“or ClickHouse Cloud if your priority is the lowest cost-performance for analytics-heavy workloads” Perplexity Sonar · budget prompt · first choice
“ClickHouse Cloud, which is described as being "Fast & Low-Cost" and suitable for large-scale data warehousing.” Llama 4 Maverick · negative prompt · alternative
“Known for high-performance, real-time analytics, especially for large-scale, low-latency queries.” Mistral Small · comparative prompt · alternative
Also compared
Comparisons are drawn for the top three products in each category. The output is the models' output; nothing here is a recommendation by the index.