Data warehouses for enterprise buyers
Asked as “cloud data warehouse”, and as “analytical data warehouse platform”, on behalf of an enterprise B2B company. 44 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
70%
Clear leader
70Snowflake20Google BigQuery05Amazon Redshift05others
70% of first choices, clear leader.
Since October 2026▲+8Since October 2026: 62% → 70%, +8 points. Inside the 11-point floor: within noise.Snowflake held the lead, +8 points on 62%, inside the 11-point floor.
By buyer segment
The same question asked on behalf of a different buyer. Each standing is computed within its segment; they sit side by side and are never added together.
Small business
Google BigQuery69%Clear leader▲+6Since October 2026: 63% → 69%, +6 points. Inside the 11-point floor: within noise.Standing →Mid-market
Snowflake62%Clear leader▲+13Since October 2026: 49% → 62%, +13 points. Past the 11-point floor: movement.Standing →EnterpriseSnowflake70%Clear leader▲+8Since October 2026: 62% → 70%, +8 points. Inside the 11-point floor: within noise.This page
Google BigQuery69%Clear leader▲+6Since October 2026: 63% → 69%, +6 points. Inside the 11-point floor: within noise.Standing →Mid-marketSnowflake62%Clear leader▲+13Since October 2026: 49% → 62%, +13 points. Past the 11-point floor: movement.Standing →EnterpriseSnowflake70%Clear leader▲+8Since October 2026: 62% → 70%, +8 points. Inside the 11-point floor: within noise.This pageThe standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all fourteen models, for an enterprise B2B company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince October 2026
01Snowflake70%24%78endorsed leader▲+8Since October 2026: 62% → 70%, +8 points. Inside the 11-point floor: within noise.62% → 70%
Snowflake70%24%78endorsed leader▲+8Since October 2026: 62% → 70%, +8 points. Inside the 11-point floor: within noise.62% → 70%02Google BigQuery Lab in the set20%19%78accepted challenger▲+1Since October 2026: 19% → 20%, +1 point. Inside the 11-point floor: within noise.19% → 20%
Google BigQuery Lab in the set20%19%78accepted challenger▲+1Since October 2026: 19% → 20%, +1 point. Inside the 11-point floor: within noise.19% → 20%03
Amazon Redshift5%23%74accepted challenger▼−7Since October 2026: 12% → 5%, −7 points. Inside the 11-point floor: within noise.12% → 5%
Amazon Redshift5%23%74accepted challenger▼−7Since October 2026: 12% → 5%, −7 points. Inside the 11-point floor: within noise.12% → 5%04Microsoft Fabric Data Warehouse5%16%32accepted challenger▲+3Since October 2026: 2% → 5%, +3 points. Inside the 11-point floor: within noise.2% → 5%
Show the four products at 0%, ordered by negative rate
08
Teradata Vantage0%42%12criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
Teradata Vantage0%42%12criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%07
ClickHouse Cloud0%30%10criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
ClickHouse Cloud0%30%10criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%05
Databricks SQL0%16%57accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
Databricks SQL0%16%57accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%06
Azure Synapse Analytics0%14%28accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
Azure Synapse Analytics0%14%28accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%The floor is 11 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one can't be told apart from repeat variation, and both are shown. Each index measures its own floor from its own repeat, over its own categories, so the floor differs from one index to the next. Both editions asked the same fourteen models. How the floor is measured
Bars are the share of first choices, 0 to 100Every product with at least 10 labels here. Every product name links to its product page.
Google BigQuery is made by Google, whose model Gemini 3.5 Flash is in the set. On the four share prompts that model made it the first choice zero times of 4; the other thirteen models nine times of 52. Lab treatment is defined on the method page; the row is marked, not excluded.
Head to headHead-to-head pages are published for mid-market buyers, so these open on mid-market figures, not enterprise.
One product takes 70% of first choices here, so the chart would put seven markers in one corner and one at the far edge. The two measurements it plots are columns in the standing above: share, and the negative label rate. Two products carry a negative rate above 25% in this category.
What they warned about
Thirteen of fourteen models held their first choice under the paraphrase. Claude Haiku 4.5 changed. A high negative share on a product with few labels is a warning. A low share on a product with many labels is salience, not sentiment.
Google BigQuery19%
15 of 78 labels negative · 14 of 14 models · 1 hard negative
“Google BigQuery (proprietary formats, high lock-in)” Mistral Small, negative prompt
Snowflake24%
19 of 78 labels negative · 13 of 14 models · 2 hard negative
“Large enterprises should be cautious about or avoid the following cloud data warehouses due to high vendor lock-in risk or poor enterprise support: - Snowflake (proprietary formats, high lock-in)” Mistral Small, negative prompt
Amazon Redshift23%
17 of 74 labels negative · 12 of 14 models · 1 hard negative
“Amazon Redshift (low user satisfaction, limited long-term viability)” Mistral Small, negative prompt
Databricks SQL16%
9 of 57 labels negative · 7 of 14 models
“Entity to be cautious about: Databricks (Lakehouse Platform) ... requires significant expertise to tune, maintain, and secure.” Qwen 3.7 Flash, negative prompt
What they cite
Fourteen of the fourteen models returned a source list in this edition: five return the pages they cited and nine the search results they consulted.
Sites the answers cite
72 of 84 answers in this category came back with a source list, from 14 of 14 models: citations where the model returns them, or the search results it consulted. 864 links across 275 sites, every framing counted. Ranked by the number of answers carrying the site or page. 30 of the 252 answers across every segment cited this index's own page for the category; the method page measures whether that reading tilts an answer.
29 answers · 55 citations · 11 models
25 answers · 28 citations · 10 models
20 answers · 20 citations · 9 models
20 answers · 20 citations · 8 models
vendor site · Google19 answers · 34 citations · 11 models
vendor site · LinkedIn16 answers · 22 citations · 5 models
15 answers · 15 citations · 7 models
vendor site · Google14 answers · 19 citations · 6 models
vendor site · Atlan14 answers · 14 citations · 9 models
vendor site · Snowflake13 answers · 18 citations · 5 models
vendor site · MotherDuck13 answers · 15 citations · 8 models
vendor site · Fivetran12 answers · 13 citations · 7 models
Pages the answers cite
The ten pages named in the most answers, by full address. A page here is one the models returned with a recommendation, not one the index endorses.
20 answers · 9 models
18 answers · 8 models
16 answers · 9 models
15 answers · 9 models
13 answers · 8 models
13 answers · 7 models
12 answers · 9 models
11 answers · 9 models
11 answers · 7 models
10 answers · 6 models
Search against answers
Each company's standing in the answers beside its site's footprint in Google search, one row a site: the products the models named on it with their shares, and the share they add up to; monthly searches on Google, and DataForSEO's estimate of AI search demand (modeled from search signals, directional, not a count of queries to any assistant), for the most-searched of the company's and its products' names (the name is in each row's hover text); estimated monthly organic visits to the site; and its best position in Google's top ten for “best cloud data warehouse”, “cloud data warehouse”, “cloud data warehouses”. US estimates from DataForSEO and Google's Ads Transparency Center. A small company's site, or a mid-sized company's site for its flagship, is marked company; a product on a large parent's site (Google, Microsoft) has no site figures. A column with no figures for this category is left out, and an empty cell means none were seen, not none exist. Two measurements side by side: neither is read as the cause of the other.
| Company and products | Share | Own site cited | Name searches, Google | AI search demand, est. | Organic visits | Paid search a month, est. | Google ads, last 30 days | Best Google position |
|---|---|---|---|---|---|---|---|---|
| Snowflake snowflake.com | 70% | 226 | 368,000 | 37,077 | 718,749 | 118 | ||
| Google BigQuery cloud.google.com | 20% | 224 | 8,100 | 359 | 7,405,347 | |||
| Amazon aws.amazon.com Amazon Redshift 5% | 5% | 193 | 151,000,000 | 1,380,939 | 9,238,321 | $20,476 | ||
| Microsoft parent site Microsoft Fabric Data Warehouse 5%, Microsoft Fabric / Azure Synapse 0%, Microsoft Fabric / Synapse 0% | 5% | 63 | 2,240,000 | 403,136 | ||||
| Databricks databricks.com Databricks SQL 0%, Databricks Unity Catalog 0% | 0% | 129 | 135,000 | 8,368 | 689,756 company | $34,664 | 120 | 6 |
| Azure azure.com Azure Synapse Analytics 0% | 0% | 51 | 301,000 | 47,904 | ||||
| ClickHouse Cloud clickhouse.com | 0% | 168 | 1,000 | 15 | 43,805 | 47 | 3 | |
| Apache Doris | 0% | |||||||
| IBM ibm.com | 0% | 168 | 201,000 | 34,098 | 31,137,701 | $2,518 | 118 | |
| Oracle oracle.com | 0% | 64 | 450,000 | 66,611 | 7,410,638 | $247 | 101 | 4 |
Google's top ten for the three searches hold 21 sites; 3 of them are among the sites the models cited here (clickhouse.com, fortegrp.com, linkedin.com). The first result for “best cloud data warehouse” is reddit.com.
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.ShowHide
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.
ShowHideModelDirect“What is the best cloud data warehouse for an enterprise B2B company?”Paraphrase“Which analytical data warehouse platform would you recommend to a large B2B company with thousands of employees?”Comparative“What are the top enterprise-grade cloud data warehouses and how do they differ?”Budget-constrained“What is the best cloud data warehouse for a large company that needs predictable total cost across thousands of users?”Scale-constrained“We are a 5,000 person company with SSO, SOC 2 and procurement review requirements evaluating a cloud data warehouse. What should we look at?”Negative“Which cloud data warehouses should a large enterprise avoid or be cautious about?”
Claude Haiku 4.5no first choiceGoogle BigQuery, SnowflakeChangedno first choiceAmazon Redshift, Microsoft Fabric Data Warehouseagainst: Google BigQuery, Snowflakeno first choiceagainst: Amazon Redshift, Google BigQuery, Snowflake
Two alternatives
Amazon Redshift, Azure Synapse AnalyticsGPT-5.4 miniSnowflakeSnowflakeHeldSnowflakeGoogle BigQueryagainst: Snowflakeno first choiceagainst: Google BigQuery, Microsoft's Fabric Data Warehouse, Teradata Vantage
Four alternatives
Amazon Redshift, Azure Synapse Analytics, Google BigQuery, Microsoft Fabric Data WarehouseThree alternatives
Amazon Redshift, Databricks SQL, Google BigQueryFour alternatives
Amazon Redshift, Azure Synapse Analytics, Google BigQuery, Microsoft Fabric Data WarehouseOne alternative
Amazon RedshiftGemini 3.5 FlashSnowflakeSnowflakeHeldSnowflakeAmazon Redshiftagainst: Snowflakeno first choiceagainst: AWS Redshift DC2/DS2 provisioned clusters, Apache Druid, Apache Pinot, ClickHouse Cloud, Databricks SQL, Google BigQuery, IBM Netezza / Db2 Warehouse, Oracle Autonomous Data Warehouse, Snowflake, StarRocks, Teradata Vantage, static Azure Synapse dedicated SQL pools
Four alternatives
Amazon Redshift, Databricks SQL, Google BigQuery, Microsoft Fabric Data WarehouseFive alternatives
Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQuery, Microsoft Fabric Data WarehouseFive alternatives
Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQuery, Microsoft Fabric Data WarehouseTwo alternatives
Google BigQuery, Microsoft Fabric / Azure SynapsePerplexity SonarSnowflakeSnowflakeHeldAmazon Redshift, Google BigQuery, SnowflakeMicrosoft Fabric Data Warehouseagainst: Snowflakeno first choiceagainst: Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQuery, Microsoft Fabric Data Warehouse, Oracle Autonomous Data Warehouse, SAP Datasphere, Snowflake
Four alternatives
Amazon Redshift, Databricks SQL, Google BigQuery, Microsoft Fabric Data WarehouseThree alternatives
Databricks SQL, Google BigQuery, Microsoft Fabric Data WarehouseThree alternatives
Azure Synapse Analytics, Databricks SQL, Microsoft Fabric Data WarehouseTwo alternatives
Amazon Redshift, Google BigQueryGrok 4.20SnowflakeSnowflakeHeldGoogle BigQuery, SnowflakeSnowflakeagainst: Amazon Redshift, ClickHouse Cloud, Databricks SQL, Firebolt, Microsoft Fabric Data WarehouseSnowflakeagainst: Cloudera, Teradata Vantageagainst: Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQuery, Microsoft Fabric Data Warehouse, Snowflake
Four alternatives
Amazon Redshift, Databricks SQL, Google BigQuery, Microsoft Fabric Data WarehouseFour alternatives
Amazon Redshift, Databricks SQL, Google BigQuery, Microsoft Fabric Data WarehouseTwo alternatives
Amazon Redshift, Azure Synapse AnalyticsOne alternative
Google BigQueryThree alternatives
Amazon Redshift, Databricks SQL, Google BigQueryMistral SmallSnowflakeSnowflakeHeldno first choiceGoogle BigQueryagainst: SnowflakeSnowflakeagainst: Amazon Redshift, Microsoft Fabric Data Warehouseagainst: Amazon Redshift, Azure Synapse Analytics, Google BigQuery, Snowflake
Two alternatives
Amazon Redshift, Google BigQueryFour alternatives
Amazon Redshift, Databricks SQL, Google BigQuery, Microsoft Fabric Data WarehouseTwo alternatives
Amazon Redshift, ClickHouse CloudTwo alternatives
Databricks SQL, Google BigQueryDeepSeek V4 FlashSnowflakeagainst: Amazon RedshiftSnowflakeHeldSnowflakeGoogle BigQueryno first choiceagainst: Databricks SQLagainst: Amazon RDS, Amazon Redshift, Apache Druid, ClickHouse Cloud, Google BigQuery, Heroku Postgres-based warehouses, IBM Db2 Warehouse, Oracle Autonomous Warehouse, Panoply, SAP Data Warehouse Cloud, Snowflake, StarRocks, Teradata Vantage
Three alternatives
Databricks SQL, Google BigQuery, Microsoft Fabric / SynapseFour alternatives
Amazon Redshift, Databricks SQL, Google BigQuery, Microsoft Fabric Data WarehouseFour alternatives
Amazon Redshift, Databricks SQL, Google BigQuery, Microsoft Fabric / Azure SynapseOne alternative
SnowflakeLlama 4 MaverickSnowflakeSnowflakeHeldClickHouse Cloudno first choiceno first choiceagainst: Amazon Redshift, Google BigQuery, Snowflake
Four alternatives
Amazon Redshift, Databricks SQL, Google BigQuery, Teradata VantageFour alternatives
Amazon Redshift, Databricks SQL, Google BigQuery, Teradata VantageQwen 3.7 FlashSnowflakeSnowflakeHeldSnowflakeGoogle BigQueryagainst: Amazon Redshiftno first choiceagainst: Amazon Redshift, Databricks SQL, Google BigQuery, Snowflake
Three alternatives
Amazon Redshift, Databricks SQL, Google BigQueryThree alternatives
Amazon Redshift, Databricks SQL, Microsoft Fabric Data WarehouseFive alternatives
Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQuery, Microsoft Fabric Data WarehouseTwo alternatives
ClickHouse Cloud, SnowflakeKimi K2SnowflakeSnowflakeHeldDatabricks SQL, SnowflakeGoogle BigQueryagainst: Amazon Redshiftno first choiceagainst: Databricks SQL, Snowflakeagainst: Amazon Redshift, Databricks SQL, Google BigQuery, IBM Netezza, Oracle Exadata Cloud, Snowflake, Teradata Vantage
Three alternatives
Amazon Redshift, Google BigQuery, Microsoft Fabric / Azure SynapseFive alternatives
Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQuery, Microsoft Fabric Data WarehouseFour alternatives
Amazon Redshift, Azure Synapse Analytics, Google BigQuery, Microsoft Fabric Data WarehouseThree alternatives
Azure Synapse Analytics, Microsoft Fabric Data Warehouse, SnowflakeTwo alternatives
Amazon Redshift, Google BigQueryGLM 4.7 FlashXSnowflakeSnowflakeHeldSnowflakeGoogle BigQueryno first choiceagainst: Amazon Redshift, Azure Synapse Analytics, Cloudera Data Platform, Google BigQuery, Microsoft Fabric Data Warehouse, Teradata VantageCloud
Three alternatives
Amazon Redshift, Azure Synapse Analytics, Google BigQueryTwo alternatives
Amazon Redshift, Google BigQueryFour alternatives
Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQueryOne alternative
Amazon RedshiftMiniMax M2.5SnowflakeSnowflakeHeldno first choiceGoogle BigQueryno first choiceagainst: Amazon Redshift, Google BigQuery, Snowflake
Four alternatives
Amazon Redshift, Databricks SQL, Google BigQuery, Microsoft Fabric / SynapseThree alternatives
Amazon Redshift, Azure Synapse Analytics, Databricks SQLThree alternatives
Amazon Redshift, Azure Synapse Analytics, SnowflakeGPT-6 LunaSnowflakeSnowflakeHeldno first choiceGoogle BigQueryagainst: Snowflakeno first choiceagainst: Amazon Redshift, Azure Synapse Dedicated SQL pool, Databricks SQL, Google BigQuery, Snowflake
Three alternatives
Amazon Redshift, Databricks SQL, Google BigQueryThree alternatives
Amazon Redshift, Databricks SQL, Google BigQueryOne alternative
Amazon RedshiftMuse Glimmer 30BSnowflakeSnowflakeHeldSnowflakeSnowflakeno first choiceagainst: Amazon Redshift, Google BigQuery, Snowflake
Three alternatives
Amazon Redshift, Databricks SQL, Google BigQueryTwo alternatives
Databricks SQL, Google BigQueryFive alternatives
Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQuery, Microsoft Fabric Data WarehouseOne alternative
Google BigQueryBold is the first choiceAlternatives are counted; the count opens them.What the answer argued against
The record
One row per call: the version string exactly as returned, whether the model searched, sources cited, and latency.
Eighty-four rows: every prompt, every model, every answer.
| Prompt | Model | Version string | Time (UTC) | Searched | Sources | Latency |
|---|---|---|---|---|---|---|
| Direct recommendation | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 17:37 | no | 0 | 5 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 08:35 | yes | 3 | 4 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 13:57 | yes | 8 | 24 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-11-01 15:36 | yes | 10 | 4 s |
| Direct recommendation | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 17:31 | yes | 5 | 12 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 11:41 | yes | 5 | 3 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 13:48 | yes | 24 | 26 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 19:15 | yes | 5 | 3 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 11:59 | yes | 10 | 27 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 10:08 | yes | 10 | 48 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 12:03 | yes | 24 | 37 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 16:29 | yes | 10 | 53 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-11-01 17:59 | yes | 4 | 11 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 16:34 | yes | 14 | 23 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 10:35 | no | 0 | 5 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 16:41 | yes | 5 | 5 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 15:02 | no | 0 | 18 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-11-01 10:35 | yes | 10 | 3 s |
| Paraphrase | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 18:56 | yes | 5 | 9 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 16:30 | yes | 5 | 5 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 11:04 | yes | 22 | 21 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 13:32 | yes | 5 | 3 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 19:10 | yes | 5 | 25 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 17:36 | yes | 15 | 23 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 10:53 | yes | 15 | 81 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 11:41 | no | 0 | 13 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-11-01 12:21 | yes | 5 | 10 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 10:05 | yes | 13 | 17 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 19:26 | yes | 9 | 8 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 09:19 | yes | 9 | 8 s |
| Comparative | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 10:27 | no | 0 | 18 s |
| Comparative | Perplexity Sonar | sonar | 2026-11-01 18:35 | yes | 10 | 6 s |
| Comparative | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 13:50 | yes | 5 | 13 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 12:13 | yes | 10 | 8 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 09:53 | yes | 18 | 25 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 15:39 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 15:37 | yes | 5 | 30 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 13:25 | yes | 10 | 46 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 16:01 | yes | 25 | 227 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 15:59 | yes | 5 | 15 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-11-01 18:31 | yes | 8 | 19 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 17:03 | yes | 14 | 29 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 12:07 | yes | 18 | 10 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 09:25 | yes | 5 | 6 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 10:06 | no | 0 | 19 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-11-01 18:14 | yes | 10 | 3 s |
| Budget constrained | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 18:14 | yes | 14 | 13 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 17:04 | yes | 5 | 7 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 14:56 | yes | 24 | 33 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 08:50 | yes | 5 | 3 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 13:26 | yes | 5 | 15 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 17:47 | yes | 15 | 42 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 13:28 | yes | 14 | 21 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 09:58 | yes | 24 | 133 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-11-01 16:58 | yes | 3 | 14 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 14:26 | yes | 24 | 37 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 10:23 | yes | 18 | 10 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 17:07 | no | 0 | 10 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 15:30 | no | 0 | 16 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-11-01 17:28 | yes | 10 | 8 s |
| Scale constrained | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 16:57 | yes | 5 | 15 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 16:06 | no | 0 | 10 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 18:33 | yes | 24 | 82 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 10:44 | yes | 5 | 2 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 09:05 | no | 0 | 29 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 12:16 | yes | 24 | 37 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 10:46 | yes | 23 | 35 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 19:36 | no | 0 | 18 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-11-01 15:11 | yes | 3 | 21 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 09:25 | yes | 25 | 32 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 18:13 | yes | 20 | 10 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 10:33 | yes | 5 | 7 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 15:43 | no | 0 | 21 s |
| Negative framing | Perplexity Sonar | sonar | 2026-11-01 11:54 | yes | 10 | 9 s |
| Negative framing | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 18:53 | yes | 13 | 17 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 11:59 | yes | 14 | 28 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 15:05 | yes | 24 | 46 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 14:44 | yes | 5 | 3 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 16:33 | yes | 10 | 50 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 13:13 | yes | 15 | 102 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 13:31 | yes | 22 | 69 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 13:06 | yes | 25 | 137 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-11-01 13:17 | yes | 5 | 16 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 12:41 | yes | 23 | 24 s |
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
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Category-scoped readings
Azure Synapse read as Azure Synapse Analytics
Databricks read as Databricks SQL
Databricks (Lakehouse Platform) read as Databricks SQL
Databricks (Lakehouse) read as Databricks SQL
Databricks (SQL Warehouses) read as Databricks SQL
Databricks (using Delta Lake) read as Databricks SQL
Databricks (with Lakehouse/SQL Warehouses) read as Databricks SQL
Databricks Lakehouse read as Databricks SQL
Fabric read as Microsoft Fabric Data Warehouse
Microsoft Fabric read as Microsoft Fabric Data Warehouse
Microsoft Fabric (OneLake) read as Microsoft Fabric Data Warehouse
Microsoft Fabric (or Azure Synapse Analytics) read as Microsoft Fabric Data Warehouse
Microsoft Fabric Warehouse read as Microsoft Fabric Data Warehouse
Teradata read as Teradata Vantage
Unresolved, counted raw
AWS Redshift DC2/DS2 provisioned clusters
Apache Doris
Azure Synapse Dedicated SQL pool
Heroku Postgres-based warehouses
IBM Netezza
Microsoft's Fabric Data Warehouse
Oracle Autonomous Warehouse
Oracle Exadata Cloud
Redshift RA3 nodes or Redshift Serverless
SAP Data Warehouse Cloud
VMware Greenplum
Vertica
static Azure Synapse dedicated SQL pools (DWUs)
Discontinued, still offered
No shut-down product was recommended here.