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Data warehouses · November 2026 Edition

Google BigQuery vs ClickHouse Cloud

Two of fourteen models named Google BigQuery first on the direct prompt; zero named ClickHouse Cloud. Google BigQuery was named by fourteen of the fourteen models and ClickHouse Cloud by eleven and Google BigQuery carries 78 labels and ClickHouse Cloud 26, so the shares are not directly comparable.

Google BigQuery

endorsed leader

Named in three categories this edition.

ClickHouse Cloud

accepted challenger

Named in six categories this edition.

First-choice share33%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate13%12%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#3A position in a field of 8; printed, not drawn.
Labels7826A 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 fourteen of the fourteen 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 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 warehouses page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
Google BigQueryFirst choices, of fourteen modelsClickHouse Cloud
Direct20
Paraphrase201 against ClickHouse Cloud
Comparative201 against ClickHouse Cloud
Budget-constrained132
Scale-constrained001 against ClickHouse Cloud
Negative0010 against Google BigQuery
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Across every category in the November 2026 Edition, Google BigQuery and ClickHouse Cloud were named in the same answer sixty-two times, of the 274 answers naming Google BigQuery and the 204 naming ClickHouse Cloud. In those answers ClickHouse Cloud took the first choice one time and Google BigQuery twenty-five.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Google BigQuery and ClickHouse Cloud stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
Google BigQuery ClickHouse Cloud first choice named as an alternative argued againstblank: not namedEach cell is one answer, Google BigQuery on the left and ClickHouse Cloud on the right.

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

2 of 14 modelsClickHouse Cloud was named in the answer but not as the choice, or not at all.
Qwen 3.7 FlashGoogle BigQuery, Snowflake alternatives: Amazon Redshift, Databricks SQL
Muse Glimmer 30BGoogle BigQuery, Snowflake alternatives: Amazon Redshift, Databricks SQL

Neither was the first choice, one was named

11 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Snowflake alternatives: Amazon Redshift, Azure SQL Database or Azure Synapse, ClicData, Firebolt, Google BigQuery, Panoply
GPT-5.4 miniSnowflake alternatives: Amazon Redshift, Google BigQuery
Gemini 3.5 FlashSnowflake alternatives: Amazon Redshift, Azure Synapse Analytics, Google BigQuery, Microsoft Fabric Data Warehouse
Perplexity SonarSnowflake alternatives: Amazon Redshift, ClickHouse Cloud, Databricks SQL, Google BigQuery, Microsoft Fabric Data Warehouse
Grok 4.20Snowflake alternatives: Amazon Redshift, Databricks SQL, Google BigQuery, Microsoft Fabric Data Warehouse
Mistral SmallSnowflake alternatives: Amazon Redshift, Databricks SQL, Google BigQuery
DeepSeek V4 FlashSnowflake alternatives: Amazon Redshift, Databricks SQL, Google BigQuery
Kimi K2Snowflake alternatives: Amazon Redshift, Google BigQuery
GLM 4.7 FlashXSnowflake alternatives: Amazon Redshift, Azure Synapse Analytics, Google BigQuery
MiniMax M2.5Snowflake alternatives: Amazon Redshift, Azure Synapse Analytics, Google BigQuery
GPT-6 LunaSnowflake alternatives: Amazon Redshift, Databricks SQL, Google BigQuery

Neither was named

1 of 14 modelsThe answer made no first choice from these two in this category.
Llama 4 MaverickSnowflake

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 sixty-eight points.
Google BigQuery69%#1 of 10
ClickHouse Cloud2%#5 of 10
The full small business standing →
Mid-marketThe figures above
Google BigQuery leads by twenty-nine points.
Google BigQuery33%#2 of 8
ClickHouse Cloud4%#3 of 8
The full mid-market standing →
Enterprise
Google BigQuery leads by twenty points.
Google BigQuery20%#2 of 8
ClickHouse Cloud0%#7 of 8
The full enterprise standing →

What 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.

“Tools like Snowflake, BigQuery, and Redshift are optimized for structured business intelligence (BI) and reporting.” Mistral Small · negative prompt · soft negative
“Be Cautionary If: You are not already on Google Cloud Platform (GCP) or need flexible capacity management.” Qwen 3.7 Flash · negative prompt · soft negative
“BigQuery is an excellent product, but you must implement strict quotas, cost controls, query limits” Gemini 3.5 Flash · negative prompt · soft negative
“For most small-to-mid-sized companies on a limited budget, Google BigQuery is arguably the best starting point” DeepSeek V4 Flash · budget prompt · first choice
“the most common "safe bet" is Snowflake or Google BigQuery because they abstract away cluster management” MiniMax M2.5 · comparative prompt · first choice
“Start with BigQuery if you are cost-conscious, have variable data volumes, or are already on Google Cloud.” Qwen 3.7 Flash · direct 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. Five of five in this category shown.

“often favor specialized engines like ClickHouse for cost/performance at scale” Grok 4.20 · comparative prompt · soft negative
“more specialized and less "all‑in‑one" for a typical mid‑size B2B stack” GLM 4.7 FlashX · paraphrase prompt · soft negative
“Best for Raw Cost Efficiency: ClickHouse Cloud ... order-of-magnitude better value (often 10x cheaper)” Qwen 3.7 Flash · budget prompt · first choice
“ClickHouse Cloud is consistently shown as the cost-performance leader.” Muse Glimmer 30B · budget prompt · first choice
“if your workloads are event-centric and latency-sensitive, ClickHouse or Firebolt will likely give you the best price-performance” MiniMax M2.5 · comparative prompt · alternative
Also compared

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.