Data warehouses for small business buyers
Asked as “cloud data warehouse”, and as “analytical data warehouse platform”, on behalf of a small B2B company. 59 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
63%
Clear leader
63Google BigQuery24Snowflake05Amazon Redshift08others
63% of first choices, clear leader.
Since September 2026▼−18Since September 2026: 80% → 62%, −18 points. Past the 11-point floor: movement. Read over the models both editions asked.Google BigQuery held the lead, −18 points on 80%, past the 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.This pageMid-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.Standing →
Google BigQuery63%Clear leader▼−18Since September 2026: 80% → 62%, −18 points. Past the 11-point floor: movement. Read over the models both editions asked.This pageMid-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.Standing →The standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all fourteen models, for a small B2B company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince September 2026
01Google BigQuery Lab in the set63%14%77endorsed leader▼−18Since September 2026: 80% → 62%, −18 points. Past the 11-point floor: movement. Read over the models both editions asked.80% → 62%
Google BigQuery Lab in the set63%14%77endorsed leader▼−18Since September 2026: 80% → 62%, −18 points. Past the 11-point floor: movement. Read over the models both editions asked.80% → 62%02Snowflake24%34%73criticized challenger▲+16Since September 2026: 12% → 28%, +16 points. Past the 11-point floor: movement. Read over the models both editions asked.12% → 28%
Snowflake24%34%73criticized challenger▲+16Since September 2026: 12% → 28%, +16 points. Past the 11-point floor: movement. Read over the models both editions asked.12% → 28%03
MotherDuck5%3%30accepted challenger▲+2Since September 2026: 2% → 4%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 4%
MotherDuck5%3%30accepted challenger▲+2Since September 2026: 2% → 4%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 4%04
Amazon Redshift5%28%72criticized challenger=heldSince September 2026: 4% → 4%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.4% → 4%
Amazon Redshift5%28%72criticized challenger=heldSince September 2026: 4% → 4%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.4% → 4%Show the four products at 0%, ordered by negative rate
08
Databricks SQL0%50%30criticized 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%50%30criticized 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%18%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%
05
ClickHouse Cloud0%10%29accepted 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%10%29accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%07
PostgreSQL0%10%10accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
PostgreSQL0%10%10accepted 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 three times of 4; the other thirteen models thirty-four 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
Recommended versus criticized
Every product with at least 10 labels here, on both axes. The 30% line names a quadrant, not the verdict above: that one needs more than 40%.
Criticized challengerCriticized default
Negative label rate →
0102030405A06
0708Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative80%
Key
01Google BigQuery63%
Google BigQuery63%02Snowflake24%
Snowflake24%03MotherDuck5%
MotherDuck5%04Amazon Redshift5%
Amazon Redshift5%05ClickHouse Cloud0%
ClickHouse Cloud0%06Azure Synapse Analytics0%
07PostgreSQL0%
PostgreSQL0%08Databricks SQL0%
Databricks SQL0%What they warned about
Five of fourteen models held their first choice under the paraphrase. Claude Haiku 4.5, GPT-5.4 mini, Gemini 3.5 Flash, Perplexity Sonar, Mistral Small, Llama 4 Maverick, GLM 4.7 FlashX, MiniMax M2.5 and Muse Glimmer 30B 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.
Snowflake34%
25 of 73 labels negative · 13 of 14 models · 4 hard negative
“small businesses are often cautioned to avoid or at least pilot very carefully: Snowflake – high baseline costs and compliance features behind premium editions, unpredictable compute billing” Muse Glimmer 30B, negative prompt
Amazon Redshift28%
20 of 72 labels negative · 12 of 14 models · 3 hard negative
“Why to avoid: Redshift ... the "Provisioned" cluster version requires significant manual maintenance.” Gemini 3.5 Flash, negative prompt
Google BigQuery14%
11 of 77 labels negative · 11 of 14 models · 1 hard negative
“Google BigQuery – ... can be costly for low-volume, ad-hoc queries” Muse Glimmer 30B, negative prompt
Databricks SQL50%
15 of 30 labels negative · 9 of 14 models · 2 hard negative
“Why to avoid: Databricks is a phenomenal platform for massive data science... the engineering overhead and administrative complexity of Databricks are an expensive nightmare.” Gemini 3.5 Flash, 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
73 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. 964 links across 212 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.
39 answers · 57 citations · 13 models
vendor site · OvalEdge38 answers · 38 citations · 12 models
vendor site · MotherDuck36 answers · 72 citations · 13 models
36 answers · 36 citations · 12 models
vendor site · Fivetran26 answers · 31 citations · 9 models
vendor site · Atlan25 answers · 26 citations · 8 models
vendor site · Airbyte18 answers · 18 citations · 8 models
17 answers · 18 citations · 7 models
17 answers · 17 citations · 7 models
vendor site · Tinybird17 answers · 17 citations · 10 models
15 answers · 22 citations · 7 models
vendor site · Accio15 answers · 19 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.
38 answers · 12 models
36 answers · 12 models
30 answers · 11 models
25 answers · 8 models
24 answers · 9 models
17 answers · 8 models
16 answers · 7 models
16 answers · 7 models
16 answers · 10 models
14 answers · 9 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 |
|---|---|---|---|---|---|---|---|---|
| Google BigQuery cloud.google.com | 63% | 224 | 8,100 | 359 | 7,405,347 | |||
| Snowflake snowflake.com | 24% | 228 | 368,000 | 37,077 | 718,749 | 118 | ||
| MotherDuck motherduck.com | 5% | 42 | 5,400 | 66 | 22,212 | 30 | ||
| Amazon aws.amazon.com Amazon Redshift 5%, Amazon Athena 0% | 5% | 198 | 151,000,000 | 1,380,939 | 9,238,321 | $20,476 | ||
| DuckDB duckdb.org | 2% | 14 | 18,100 | 686 | 15,468 | |||
| Snowflake's Standard edition | 2% | |||||||
| ClickHouse Cloud clickhouse.com | 0% | 178 | 1,000 | 15 | 43,805 | 47 | 3 | |
| Azure Synapse Analytics | 0% | 301,000 | 47,904 | |||||
| PostgreSQL postgresql.org | 0% | 82 | 74,000 | 14,143 | 465,585 | |||
| Firebolt firebolt.io | 0% | 8 | 4,400 | 923 | 6,620 | 0 |
Google's top ten for the three searches hold 21 sites; 2 of them are among the sites the models cited here (clickhouse.com, fortegrp.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 a small B2B company?”Paraphrase“Which analytical data warehouse platform would you recommend to a small business that sells to other businesses?”Comparative“What are the top cloud data warehouses for a small team and how do they differ?”Budget-constrained“What is the best cloud data warehouse for a small company with a tight budget?”Scale-constrained“We are a 30 person company evaluating a cloud data warehouse. What should we look at?”Negative“Which cloud data warehouses should a small business avoid or be cautious about?”
Claude Haiku 4.5Google BigQuery, SnowflakeSnowflakeChangedMotherDuckGoogle BigQueryno first choiceagainst: Amazon Redshift, Azure SQL Database, Azure Synapse Analytics, Snowflake
Three alternatives
Amazon Redshift, Databricks SQL, DuckDBFour alternatives
Amazon Redshift, Databricks SQL, Google BigQuery, PostgreSQL with cloud hostingFour alternatives
Firebolt, Google BigQuery, Panoply, SnowflakeOne alternative
PanoplyGPT-5.4 miniSnowflakeagainst: Amazon RedshiftGoogle BigQueryChangedGoogle BigQuery, SnowflakeGoogle BigQueryagainst: Snowflakeno first choiceagainst: Amazon Redshift, Databricks SQL, Google BigQuery, Snowflake
One alternative
Google BigQueryFour alternatives
Amazon Redshift, Azure Synapse Analytics, PostgreSQL, SnowflakeThree alternatives
Amazon Redshift, Azure Synapse Analytics, Microsoft Fabric Data WarehouseOne alternative
Amazon RedshiftGemini 3.5 FlashGoogle BigQueryMotherDuckChangedGoogle BigQuery, MotherDuckGoogle BigQueryagainst: Amazon Redshift, SnowflakeGoogle BigQueryagainst: Amazon Redshiftagainst: Amazon Redshift, Databricks SQL, Google BigQuery, Microsoft Fabric / Azure Synapse, Oracle Autonomous Data Warehouse, Snowflake, Teradata Vantage
Four alternatives
Amazon Redshift, MotherDuck, Mozart Data, SnowflakeTwo alternatives
Google BigQuery, SnowflakeTwo alternatives
Amazon Redshift, SnowflakeFive alternatives
ClickHouse Cloud, DuckDB, MotherDuck, PostgreSQL, TinybirdThree alternatives
DuckDB, MotherDuck, SnowflakePerplexity SonarSnowflakeGoogle BigQueryChangedGoogle BigQueryGoogle BigQueryagainst: Amazon Redshift, Microsoft Fabric Data Warehouse, Snowflakeno first choiceagainst: Amazon Redshift, Databricks SQL, Google BigQuery, Snowflake
Four alternatives
Amazon Redshift, ClickHouse Cloud, Google BigQuery, MotherDuckThree alternatives
ClickHouse Cloud, MotherDuck, SnowflakeFive alternatives
Amazon Redshift, ClickHouse Cloud, DuckDB, MotherDuck, SnowflakeTwo alternatives
ClickHouse Cloud, MotherDuckGrok 4.1 FastGoogle BigQueryGoogle BigQueryHeldagainst: Amazon Redshift, Databricks SQLGoogle BigQueryagainst: Databricks SQLGoogle BigQueryagainst: ClickHouse Cloud, Databricks SQL, SnowflakeGoogle BigQuery, Snowflakeagainst: Databricks SQLagainst: Amazon Redshift, Google BigQuery, Snowflake
Two alternatives
Amazon Redshift, SnowflakeOne alternative
SnowflakeTwo alternatives
Amazon Redshift, SnowflakeOne alternative
Amazon RedshiftOne alternative
Amazon RedshiftMistral SmallSnowflakeno first choiceChangedGoogle BigQuery, MotherDuckGoogle BigQueryagainst: Amazon Redshift, SnowflakeGoogle BigQuery, Snowflakeagainst: PostgreSQLagainst: Amazon Redshift, Google BigQuery, Snowflake
Three alternatives
Amazon Redshift, ClickHouse Cloud, Databricks SQLFour alternatives
Amazon Redshift, Azure Synapse Analytics, Microsoft Fabric Data Warehouse, SnowflakeOne alternative
Azure Synapse AnalyticsTwo alternatives
Amazon Redshift, FireboltDeepSeek V4 FlashGoogle BigQueryagainst: Databricks SQLGoogle BigQueryHeldagainst: ClickHouse Cloud, SnowflakeMotherDuckagainst: Amazon Redshift, SnowflakeGoogle BigQueryagainst: Snowflakeno first choiceagainst: Amazon Redshift, Databricks SQL, Google BigQuery, Snowflake
Three alternatives
Amazon Redshift, ClickHouse Cloud, SnowflakeOne alternative
Amazon RedshiftThree alternatives
ClickHouse Cloud, Databricks SQL, Google BigQueryTwo alternatives
Amazon Redshift, ClickHouse CloudThree alternatives
Amazon Redshift, Google BigQuery, SnowflakeLlama 4 Maverickno first choiceGoogle BigQuery, Snowflake's Standard editionChangedno first choiceAmazon Redshiftno first choicenothing named
One alternative
Azure Data WarehouseTwo alternatives
Databricks SQL, Google BigQueryQwen 3.7 FlashGoogle BigQuery, Snowflakeagainst: Azure Synapse AnalyticsGoogle BigQuery, SnowflakeHeldGoogle BigQueryGoogle BigQueryagainst: SnowflakeSnowflakeagainst: Apache Greenplum, Apache Spark, Cloudera, Databricks SQL, Hadoop Clusters, Hortonworks, MicroStrategy, Oracle Autonomous Database, Oracle Exadata, SAP HANA, Tableau Server, Teradata Vantage
One alternative
Amazon RedshiftOne alternative
Amazon RedshiftThree alternatives
Amazon Redshift, ClickHouse Cloud, SnowflakeTwo alternatives
Amazon Redshift, MotherDuckFour alternatives
Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQueryKimi K2Google BigQueryGoogle BigQueryHeldGoogle BigQuery, Snowflakeagainst: Databricks SQLGoogle BigQueryagainst: SnowflakeGoogle BigQuery, MotherDuckagainst: Snowflakeagainst: Amazon Redshift, Databricks SQL, Google BigQuery, Microsoft Fabric Data Warehouse, Snowflake
Two alternatives
Amazon Redshift, SnowflakeTwo alternatives
Amazon Redshift, SnowflakeOne alternative
Amazon RedshiftThree alternatives
Amazon Redshift, Neon, SupabaseGLM 4.7 FlashXGoogle BigQuery, SnowflakeGoogle BigQueryChangedagainst: Amazon RedshiftGoogle BigQueryGoogle BigQueryagainst: SnowflakeAmazon Redshift, Google BigQuery, Snowflakeagainst: Amazon Redshift, Google BigQuery, Snowflake
Two alternatives
Amazon Redshift, Databricks SQLOne alternative
SnowflakeThree alternatives
Amazon Redshift, Azure Synapse Analytics, SnowflakeOne alternative
Amazon RedshiftMiniMax M2.5Google BigQuery, SnowflakeSnowflakeChangedGoogle BigQueryagainst: MotherDuckno first choiceno first choiceagainst: Amazon Redshift, Google BigQuery, Snowflake
Two alternatives
DuckDB, MotherDuckOne alternative
Google BigQueryThree alternatives
Amazon Redshift, Databricks SQL, SnowflakeGPT-6 LunaGoogle BigQueryGoogle BigQueryHeldGoogle BigQueryagainst: ClickHouse Cloud, Databricks SQLGoogle BigQueryno first choiceagainst: Amazon Redshift, Databricks SQL, Google BigQuery, Microsoft Fabric Data Warehouse, Snowflake
Three alternatives
Amazon Redshift, Microsoft Fabric Data Warehouse, SnowflakeOne alternative
Microsoft Fabric Data WarehouseThree alternatives
Amazon Redshift, MotherDuck, SnowflakeTwo alternatives
Amazon Redshift, ClickHouse CloudMuse Glimmer 30BAmazon Redshift, Google BigQueryGoogle BigQueryChangedGoogle BigQuery, SnowflakeDuckDB, MotherDuckagainst: SnowflakeGoogle BigQueryagainst: Amazon Redshift, Azure Synapse Analytics, Databricks SQL, Google BigQuery, Snowflake
Three alternatives
ClickHouse Cloud, MotherDuck, SnowflakeTwo alternatives
Amazon Redshift, SnowflakeFour alternatives
Amazon Redshift, ClickHouse Cloud, Databricks SQL, MotherDuckThree alternatives
Amazon Athena, Amazon Redshift, Google BigQueryThree alternatives
Amazon Redshift, Microsoft Fabric Data Warehouse, SnowflakeBold 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 08:57 | no | 0 | 5 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:43 | yes | 3 | 5 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 13:41 | yes | 11 | 29 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-01 13:43 | yes | 19 | 5 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:54 | yes | 24 | 7 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 08:58 | yes | 5 | 3 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 13:04 | yes | 24 | 35 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:11 | yes | 5 | 1 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 07:51 | no | 0 | 30 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 11:07 | yes | 14 | 18 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 07:57 | yes | 13 | 66 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:38 | yes | 13 | 33 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-01 12:47 | yes | 4 | 15 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 12:16 | yes | 14 | 25 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 13:38 | no | 0 | 4 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:42 | no | 0 | 2 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 08:11 | yes | 9 | 27 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-01 13:49 | yes | 29 | 4 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 09:46 | yes | 18 | 5 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:01 | no | 0 | 1 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 13:25 | yes | 25 | 24 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 07:59 | yes | 5 | 1 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:21 | yes | 5 | 28 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:55 | yes | 20 | 19 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:00 | yes | 24 | 24 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:46 | yes | 10 | 46 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-01 10:12 | yes | 2 | 15 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:42 | yes | 12 | 39 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 07:41 | yes | 9 | 9 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 13:31 | yes | 3 | 11 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 13:24 | yes | 14 | 24 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-01 10:58 | yes | 19 | 4 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 09:44 | yes | 23 | 9 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 09:01 | yes | 15 | 13 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:55 | yes | 21 | 36 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:50 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:42 | yes | 5 | 20 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 11:17 | yes | 15 | 21 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 11:06 | yes | 24 | 97 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:32 | yes | 10 | 28 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-01 13:12 | yes | 6 | 20 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:44 | yes | 14 | 30 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 08:55 | yes | 9 | 7 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 13:15 | yes | 4 | 4 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 11:31 | yes | 16 | 26 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-01 07:42 | yes | 20 | 3 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:31 | yes | 19 | 5 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 08:41 | yes | 12 | 5 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 09:54 | yes | 25 | 27 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 08:32 | yes | 5 | 1 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 11:27 | yes | 15 | 26 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 12:03 | yes | 10 | 26 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 12:33 | yes | 25 | 44 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 09:33 | yes | 5 | 22 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 07:58 | yes | 4 | 16 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 13:02 | yes | 11 | 27 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 07:48 | no | 0 | 6 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 11:35 | no | 0 | 8 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 12:47 | no | 0 | 15 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-01 10:19 | yes | 26 | 4 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 09:44 | yes | 12 | 7 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 09:18 | no | 0 | 8 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 12:47 | yes | 18 | 58 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 09:32 | yes | 5 | 1 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 07:47 | yes | 5 | 25 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 13:06 | yes | 14 | 35 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 11:08 | no | 0 | 10 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 12:54 | yes | 5 | 32 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 07:45 | yes | 1 | 22 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:45 | yes | 14 | 27 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 12:31 | yes | 18 | 11 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:32 | yes | 3 | 5 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 13:00 | yes | 19 | 32 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-01 08:56 | yes | 17 | 4 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:07 | yes | 19 | 6 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:52 | yes | 15 | 7 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 11:08 | yes | 24 | 52 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 11:43 | yes | 5 | 1 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 13:04 | no | 0 | 29 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 11:37 | yes | 24 | 32 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 07:36 | yes | 21 | 36 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 13:02 | yes | 9 | 30 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-01 10:27 | yes | 5 | 15 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 10:14 | yes | 14 | 20 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) read as Databricks SQL
Fabric read as Microsoft Fabric Data Warehouse
Microsoft Fabric read as Microsoft Fabric Data Warehouse
Teradata read as Teradata Vantage
Unresolved, counted raw
Actian Avalanche
Apache Greenplum
Azure Data Warehouse
Definite
Hadoop Clusters (Self-Managed)
PostgreSQL with cloud hosting
Single PostgreSQL database
Snowflake's Standard edition
Tableau Server (On-Premise versions)
Discontinued, still offered
No shut-down product was recommended here.