Data warehouses for enterprise buyers
Asked as “cloud data warehouse”, and as “analytical data warehouse platform”, on behalf of an enterprise B2B company. 48 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
62%
Clear leader
62Snowflake19Google BigQuery12Amazon Redshift06others
62% of first choices, clear leader.
Since September 2026▼−10Since September 2026: 72% → 62%, −10 points. Inside the 11-point floor: within noise. Read over the models both editions asked.Snowflake held the lead, −10 points on 72%, 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 BigQuery63%Clear leader▼−18Since September 2026: 80% → 62%, −18 points. Past the 11-point floor: movement. Read over the models both editions asked.Standing →Mid-market
Snowflake49%Clear leader↗new leaderNew leader since September 2026: Google BigQuery (48%) replaces Snowflake (47% then, 48% now), 0 points clear, inside the 11-point floor.Standing →EnterpriseSnowflake62%Clear leader▼−10Since September 2026: 72% → 62%, −10 points. Inside the 11-point floor: within noise. Read over the models both editions asked.This page
Google BigQuery63%Clear leader▼−18Since September 2026: 80% → 62%, −18 points. Past the 11-point floor: movement. Read over the models both editions asked.Standing →Mid-marketSnowflake49%Clear leader↗new leaderNew leader since September 2026: Google BigQuery (48%) replaces Snowflake (47% then, 48% now), 0 points clear, inside the 11-point floor.Standing →EnterpriseSnowflake62%Clear leader▼−10Since September 2026: 72% → 62%, −10 points. Inside the 11-point floor: within noise. Read over the models both editions asked.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 September 2026
01Snowflake62%23%75endorsed leader▼−10Since September 2026: 72% → 62%, −10 points. Inside the 11-point floor: within noise. Read over the models both editions asked.72% → 62%
Snowflake62%23%75endorsed leader▼−10Since September 2026: 72% → 62%, −10 points. Inside the 11-point floor: within noise. Read over the models both editions asked.72% → 62%02Google BigQuery Lab in the set19%17%78accepted challenger▲+6Since September 2026: 13% → 19%, +6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.13% → 19%
Google BigQuery Lab in the set19%17%78accepted challenger▲+6Since September 2026: 13% → 19%, +6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.13% → 19%03
Amazon Redshift12%18%73accepted challenger▼−3Since September 2026: 15% → 12%, −3 points. Inside the 11-point floor: within noise. Read over the models both editions asked.15% → 12%
Amazon Redshift12%18%73accepted challenger▼−3Since September 2026: 15% → 12%, −3 points. Inside the 11-point floor: within noise. Read over the models both editions asked.15% → 12%04Microsoft Fabric Data Warehouse2%16%19accepted challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 2%
Show the three products at 0%, ordered by negative rate
07
ClickHouse Cloud0%24%17accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
ClickHouse Cloud0%24%17accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%06Azure Synapse Analytics0%21%38accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
05
Databricks SQL0%12%52accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
Databricks SQL0%12%52accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.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 is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. 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 one time of 4; the other thirteen models eight times of 52. Lab treatment is defined on the method page; the row is marked, not excluded.
All six head-to-head pages: the top four products, each against each
One product takes 62% of first choices here, so the chart would put six 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. Zero 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. Mistral Small 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.
Amazon Redshift18%
13 of 73 labels negative · 11 of 14 models · 2 hard negative
“the platforms to be **most cautious** about are those that combine **single-cloud dependence with high management overhead or unpredictable costs** — particularly **Amazon Redshift**” DeepSeek V4 Flash, negative prompt
Google BigQuery17%
13 of 78 labels negative · 10 of 14 models
“with Google BigQuery, a single unoptimized query can scan terabytes and cost hundreds of dollars, requiring disciplined partitioning and clustering for cost control.” Claude Haiku 4.5, negative prompt
Snowflake23%
17 of 75 labels negative · 10 of 14 models
“it is harder to make *truly* predictable without strict governance ... you can burn through credits much faster than expected, leading to unpredictable costs.” GLM 4.7 FlashX, budget prompt
Azure Synapse Analytics
21%
8 of 38 labels negative · 8 of 14 models · 3 hard negative
“Complex, fragmented architecture with four separately billed engines ... Azure-only lock-in” Kimi K2, negative prompt
What they cite
Citations exist only for the models that return a source list: fourteen of the fourteen in this edition, and all six flagship models on the expanded tier.
Sites the answers cite
75 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. 1017 links across 298 sites, every framing counted. Ranked by the number of answers carrying the site or page. 5 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.
43 answers · 44 citations · 12 models
vendor site · OvalEdge43 answers · 43 citations · 12 models
36 answers · 49 citations · 11 models
vendor site · Fivetran30 answers · 32 citations · 10 models
vendor site · MotherDuck23 answers · 29 citations · 11 models
21 answers · 22 citations · 10 models
vendor site · Atlan17 answers · 17 citations · 8 models
15 answers · 15 citations · 7 models
vendor site · Integrate.io15 answers · 15 citations · 9 models
vendor site · Databricks14 answers · 15 citations · 9 models
vendor site · Domo14 answers · 14 citations · 6 models
14 answers · 14 citations · 8 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.
43 answers · 12 models
42 answers · 12 models
28 answers · 10 models
27 answers · 10 models
20 answers · 9 models
17 answers · 8 models
15 answers · 7 models
15 answers · 9 models
13 answers · 6 models
13 answers · 8 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 | 62% | 228 | 368,000 | 37,077 | 718,749 | 118 | ||
| Google BigQuery cloud.google.com | 19% | 224 | 8,100 | 359 | 7,405,347 | |||
| Amazon aws.amazon.com Amazon Redshift 12% | 12% | 198 | 151,000,000 | 1,380,939 | 9,238,321 | $20,476 | ||
| Microsoft parent site Microsoft Fabric Data Warehouse 2%, Microsoft Fabric / Azure Synapse 2%, Microsoft Fabric / Synapse 0% | 4% | 49 | 2,240,000 | 403,136 | ||||
| MotherDuck motherduck.com | 2% | 42 | 5,400 | 66 | 22,212 | 30 | ||
| Databricks databricks.com Databricks SQL 0% | 0% | 103 | 135,000 | 8,368 | 689,756 company | $34,664 | 120 | 6 |
| Azure Synapse Analytics | 0% | 301,000 | 47,904 | |||||
| ClickHouse Cloud clickhouse.com | 0% | 178 | 1,000 | 15 | 43,805 | 47 | 3 | |
| IBM parent site IBM Db2 Warehouse 0% | 0% | 8 | 201,000 | 34,098 | ||||
| Azure parent site Azure Cosmos DB 0% | 0% | 66 | 301,000 | 47,904 |
Google's top ten for the three searches hold 21 sites; 6 of them are among the sites the models cited here (clickhouse.com, databricks.com, domo.com, fortegrp.com, integrate.io, scnsoft.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 4.5Google BigQuery, SnowflakeGoogle BigQuery, SnowflakeHeldno first choiceAmazon Redshift, Google BigQueryno first choiceagainst: Amazon Redshift, Google BigQuery
Three alternatives
Amazon Redshift, Azure Synapse Analytics, Databricks SQLThree alternatives
Amazon Redshift, Azure Synapse Analytics, Microsoft Fabric Data WarehouseOne alternative
SnowflakeGPT-5.4 miniSnowflakeSnowflakeHeldagainst: Amazon Redshiftno first choiceGoogle BigQueryno first choicenothing named
Three alternatives
Amazon Redshift, Databricks SQL, Google BigQueryTwo alternatives
Databricks SQL, Google BigQueryTwo alternatives
Amazon Redshift, Snowflake Enterprise EditionGemini 3.5 FlashSnowflakeSnowflakeHeldno first choiceGoogle BigQueryagainst: Databricks SQL, Snowflakeno first choiceagainst: Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQuery, Microsoft Fabric Data Warehouse, Oracle Autonomous Data Warehouse, Snowflake, Teradata Vantage
Three alternatives
Databricks SQL, Google BigQuery, Microsoft Fabric Data WarehouseFour alternatives
Amazon Redshift, Databricks SQL, Google BigQuery, Microsoft Fabric Data WarehouseThree alternatives
Amazon Redshift, ClickHouse Cloud, Microsoft Fabric / SynapsePerplexity SonarSnowflakeSnowflakeHeldGoogle BigQuery, SnowflakeAmazon Redshift, Microsoft Fabric / Azure Synapseagainst: Google BigQuery, Snowflakeno first choiceagainst: Amazon Redshift, Azure Synapse Analytics, Google BigQuery, Snowflake
Four alternatives
Amazon Redshift, Databricks SQL, Google BigQuery, SAP Business Data CloudTwo alternatives
Azure Synapse Analytics, IBM Db2 WarehouseThree alternatives
Amazon Redshift, Databricks SQL, Teradata VantageOne alternative
ClickHouse CloudGrok 4.1 FastSnowflakeSnowflakeHeldSnowflakeagainst: ClickHouse CloudSnowflakeagainst: Databricks SQL, Google BigQuerySnowflakeagainst: Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQuery, Snowflake
Two alternatives
Amazon Redshift, Google BigQueryTwo alternatives
Amazon Redshift, Google BigQueryFour alternatives
Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQueryTwo alternatives
Amazon Redshift, Microsoft Fabric Data WarehouseThree alternatives
Amazon Redshift, Databricks SQL, Google BigQueryMistral SmallGoogle BigQuery, MotherDuckAmazon Redshift, SnowflakeChangedno first choiceGoogle BigQueryno first choiceagainst: Cloudera Data Platform, Teradata VantageCloud, Vertica
One alternative
SnowflakeTwo alternatives
Google BigQuery, Oracle Autonomous Data WarehouseTwo alternatives
Amazon Redshift, Azure Synapse AnalyticsDeepSeek V4 FlashSnowflakeSnowflakeHeldagainst: Amazon Redshift, ClickHouse Cloud, Teradata Vantageno first choiceAmazon Redshiftagainst: Snowflakeno first choiceagainst: Amazon Redshiftagainst: Amazon Redshift, Azure Synapse Analytics, Google BigQuery, Snowflake
Three alternatives
Amazon Redshift, Databricks SQL, Google BigQueryTwo alternatives
Databricks SQL, Google BigQueryOne alternative
Google BigQueryThree alternatives
Databricks SQL, Google BigQuery, SnowflakeLlama 4 Maverickno first choiceno first choiceHeldno first choiceno first choiceno first choiceagainst: Amazon Redshift, Google BigQuery, Snowflake
Nine alternatives
Amazon Redshift, Azure Synapse Analytics, ClickHouse Cloud, Cloudera CDP, Databricks SQL, Google BigQuery, IBM Db2 Warehouse, Microsoft Fabric Data Warehouse, SnowflakeQwen 3.7 FlashSnowflakeSnowflakeHeldno first choiceGoogle BigQuerySnowflakeagainst: Amazon Aurora, Apache Druid, Apache Hive on HDFS, Azure SQL Database, Azure Synapse Analytics, ClickHouse Cloud, Cloudera, Databricks SQL, Google Cloud SQL, Hortonworks, Kyvos, Presto, RisingWave, Snowflake
Three alternatives
Amazon Redshift, Databricks SQL, Google BigQueryThree alternatives
Amazon Redshift, Databricks SQL, Google BigQueryTwo alternatives
Databricks SQL, SnowflakeThree alternatives
Azure Synapse Analytics, Databricks SQL, Google BigQueryKimi K2SnowflakeSnowflakeHeldno first choiceMicrosoft Fabric Data Warehouseagainst: BigQuery On-Demand, SnowflakeSnowflakeagainst: Google BigQueryagainst: Amazon Redshift, Azure Synapse Analytics, Google BigQuery, Snowflake
Three alternatives
Amazon Redshift, Databricks SQL, Google BigQueryThree alternatives
Databricks SQL, Google BigQuery, Microsoft Fabric / Azure SynapseTwo alternatives
Amazon Redshift, Azure Synapse AnalyticsThree alternatives
Amazon Redshift, Azure Synapse Analytics, Databricks SQLGLM 4.7 FlashXSnowflakeSnowflakeHeldno first choiceAmazon Redshiftagainst: Snowflakeno first choicenothing named
Two alternatives
Amazon Redshift, Google BigQueryTwo alternatives
Amazon Redshift, Google BigQueryFour alternatives
Amazon Redshift, Azure Synapse Analytics, Google BigQuery, SnowflakeOne alternative
Google BigQueryMiniMax M2.5SnowflakeSnowflakeHeldGoogle BigQuery, SnowflakeSnowflakeno first choiceagainst: Amazon Redshift, Azure Synapse Analytics, ClickHouse Cloud, Google BigQuery, Oracle Autonomous Data Warehouse, Teradata Vantage
Four alternatives
Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQueryThree alternatives
Amazon Redshift, Azure Synapse Analytics, Google BigQueryTwo alternatives
Amazon Redshift, Azure Synapse AnalyticsTwo alternatives
Amazon Redshift, Google BigQueryGPT-6 LunaSnowflakeSnowflakeHeldno first choiceGoogle BigQueryagainst: Snowflakeno first choiceagainst: Amazon Redshift, Azure Synapse dedicated SQL pools, Google BigQuery, Microsoft Fabric Data Warehouse, Snowflake
Three alternatives
Amazon Redshift, Databricks SQL, Google BigQueryThree alternatives
Amazon Redshift, Databricks SQL, Google BigQuerySix alternatives
Amazon Redshift, Databricks SQL, Google BigQuery, Microsoft Fabric Data Warehouse, Oracle Autonomous AI Database, SnowflakeOne alternative
Amazon RedshiftMuse Glimmer 30BSnowflakeSnowflakeHeldSnowflakeAmazon Redshiftagainst: Snowflakeno first choiceagainst: Snowflakeagainst: Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQuery, Microsoft Fabric Data Warehouse, Netezza, Oracle, Snowflake, Teradata Vantage
Three alternatives
Amazon Redshift, Azure Synapse Analytics, Google BigQueryTwo alternatives
Databricks SQL, Google BigQueryFour alternatives
Amazon Redshift, 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. Full answer text is in the free responses file. Download the record
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 | 2026-10-01 11:51 | no | 0 | 4 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 12:39 | yes | 2 | 6 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 12:52 | yes | 13 | 24 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-01 10:46 | yes | 19 | 3 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:54 | yes | 23 | 6 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 12:43 | yes | 11 | 7 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 11:10 | yes | 14 | 33 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 13:24 | yes | 5 | 3 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 12:22 | yes | 5 | 30 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 07:53 | yes | 14 | 20 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 13:06 | yes | 14 | 152 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:28 | yes | 10 | 21 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-01 12:58 | yes | 5 | 17 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 12:24 | yes | 15 | 14 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 08:19 | no | 0 | 4 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 12:02 | yes | 5 | 5 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 10:02 | yes | 12 | 20 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-01 12:35 | yes | 30 | 3 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:59 | yes | 23 | 7 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 08:53 | yes | 12 | 6 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 12:20 | yes | 25 | 30 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 08:52 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 12:09 | yes | 10 | 27 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 07:49 | yes | 14 | 15 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:59 | yes | 14 | 25 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 13:42 | yes | 10 | 25 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-01 12:06 | yes | 4 | 12 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:17 | yes | 15 | 20 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 07:51 | yes | 9 | 7 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 09:19 | yes | 6 | 7 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:05 | yes | 16 | 32 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-01 12:57 | yes | 18 | 6 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 11:36 | yes | 22 | 9 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:44 | yes | 9 | 7 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 07:59 | yes | 23 | 40 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:18 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 13:38 | yes | 10 | 28 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 13:50 | yes | 14 | 24 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:08 | yes | 20 | 113 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 12:20 | yes | 5 | 13 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-01 11:07 | yes | 6 | 18 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:25 | yes | 23 | 32 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 13:49 | yes | 17 | 9 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 12:27 | yes | 3 | 5 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 08:25 | yes | 26 | 29 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-01 08:05 | yes | 19 | 4 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 11:33 | yes | 23 | 14 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 09:36 | yes | 5 | 3 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 12:04 | yes | 23 | 52 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 13:31 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 12:52 | yes | 5 | 53 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 10:30 | yes | 24 | 27 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 12:52 | yes | 24 | 55 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 10:14 | yes | 21 | 97 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 11:07 | yes | 3 | 13 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 12:00 | yes | 11 | 26 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 10:21 | yes | 18 | 10 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 11:46 | yes | 6 | 7 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 11:02 | no | 0 | 17 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-01 08:25 | yes | 17 | 5 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 07:46 | yes | 18 | 11 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:46 | no | 0 | 10 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:03 | yes | 23 | 62 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 08:33 | yes | 5 | 3 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 12:25 | no | 0 | 43 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 09:23 | no | 0 | 26 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:29 | yes | 15 | 21 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:55 | no | 0 | 51 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:19 | yes | 2 | 19 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 12:42 | yes | 14 | 25 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 10:49 | yes | 16 | 10 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 09:45 | no | 0 | 7 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 13:45 | yes | 10 | 38 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-01 10:50 | yes | 15 | 3 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:38 | yes | 20 | 9 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:35 | yes | 5 | 4 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:34 | yes | 25 | 31 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 08:49 | yes | 5 | 2 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 08:06 | no | 0 | 35 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 07:50 | yes | 24 | 25 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 13:40 | yes | 14 | 81 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:03 | yes | 14 | 66 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-01 13:31 | yes | 5 | 25 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:06 | yes | 22 | 30 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 Architecture) read as Databricks SQL
Databricks (Lakehouse) read as Databricks SQL
Databricks SQL / Lakehouse read as Databricks SQL
Fabric read as Microsoft Fabric Data Warehouse
Microsoft Fabric read as Microsoft Fabric Data Warehouse
Microsoft Fabric Warehouse read as Microsoft Fabric Data Warehouse
Teradata read as Teradata Vantage
Teradata (Cloud) read as Teradata Vantage
Unresolved, counted raw
Apache Hive on HDFS
Azure Synapse dedicated SQL pools
BigQuery On-Demand
Cloudera CDP
Databricks Lakehouse Platform
Kyvos
Netezza
SAP Datawarehouse Cloud
Snowflake Enterprise Edition
Vertica
Discontinued, still offered
No shut-down product was recommended here.