Data warehouse and reverse ETL for marketing for enterprise buyers
Asked as “marketing data warehouse and reverse ETL stack”, and as “reverse ETL and warehouse setup for a marketing team”, on behalf of an enterprise B2B company. 98 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
47%
Clear leader
47Hightouch32Snowflake10Census11others
47% of first choices, clear leader.
Since October 2026▲+4Since October 2026: 43% → 47%, +4 points. Inside the 11-point floor: within noise.Hightouch held the lead, +4 points on 43%, 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
BigQuery44%Clear leader↗new leaderNew leader since October 2026: BigQuery (44%) replaces Hightouch (41% then, 40% now), 4 points clear, inside the 11-point floor.Standing →Mid-market
Hightouch38%Contested▼−2Since October 2026: 40% → 38%, −2 points. Inside the 11-point floor: within noise.Standing →EnterpriseHightouch47%Clear leader▲+4Since October 2026: 43% → 47%, +4 points. Inside the 11-point floor: within noise.This page
BigQuery44%Clear leader↗new leaderNew leader since October 2026: BigQuery (44%) replaces Hightouch (41% then, 40% now), 4 points clear, inside the 11-point floor.Standing →Mid-marketHightouch38%Contested▼−2Since October 2026: 40% → 38%, −2 points. Inside the 11-point floor: within noise.Standing →EnterpriseHightouch47%Clear leader▲+4Since October 2026: 43% → 47%, +4 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
01Hightouch47%5%81endorsed leader▲+4Since October 2026: 43% → 47%, +4 points. Inside the 11-point floor: within noise.43% → 47%
Hightouch47%5%81endorsed leader▲+4Since October 2026: 43% → 47%, +4 points. Inside the 11-point floor: within noise.43% → 47%02
Snowflake32%12%76endorsed leader▲+3Since October 2026: 29% → 32%, +3 points. Inside the 11-point floor: within noise.29% → 32%
Snowflake32%12%76endorsed leader▲+3Since October 2026: 29% → 32%, +3 points. Inside the 11-point floor: within noise.29% → 32%03
Census10%19%85accepted challenger▼−3Since October 2026: 13% → 10%, −3 points. Inside the 11-point floor: within noise.13% → 10%
Census10%19%85accepted challenger▼−3Since October 2026: 13% → 10%, −3 points. Inside the 11-point floor: within noise.13% → 10%04BigQuery Lab in the set7%6%64accepted challenger▲+1Since October 2026: 6% → 7%, +1 point. Inside the 11-point floor: within noise.6% → 7%
BigQuery Lab in the set7%6%64accepted challenger▲+1Since October 2026: 6% → 7%, +1 point. Inside the 11-point floor: within noise.6% → 7%05
Fivetran1%6%33accepted challenger▲+1Since October 2026: 0% → 1%, +1 point. Inside the 11-point floor: within noise.0% → 1%
Fivetran1%6%33accepted challenger▲+1Since October 2026: 0% → 1%, +1 point. Inside the 11-point floor: within noise.0% → 1%06
Polytomic1%33%18criticized challenger▼−1Since October 2026: 2% → 1%, −1 point. Inside the 11-point floor: within noise.2% → 1%
Polytomic1%33%18criticized challenger▼−1Since October 2026: 2% → 1%, −1 point. Inside the 11-point floor: within noise.2% → 1%Show the six products at 0%, ordered by negative rate
12
Segment0%39%28criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
Segment0%39%28criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%11
Amazon Redshift0%28%32criticized challenger▼−1Since October 2026: 1% → 0%, −1 point. Inside the 11-point floor: within noise.1% → 0%
Amazon Redshift0%28%32criticized challenger▼−1Since October 2026: 1% → 0%, −1 point. Inside the 11-point floor: within noise.1% → 0%09
RudderStack Reverse ETL0%21%43accepted challenger▼−1Since October 2026: 1% → 0%, −1 point. Inside the 11-point floor: within noise.1% → 0%
RudderStack Reverse ETL0%21%43accepted challenger▼−1Since October 2026: 1% → 0%, −1 point. Inside the 11-point floor: within noise.1% → 0%10
Airbyte0%12%32accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
Airbyte0%12%32accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%07
Databricks SQL Warehouse0%9%44accepted challenger▼−1Since October 2026: 1% → 0%, −1 point. Inside the 11-point floor: within noise.1% → 0%
Databricks SQL Warehouse0%9%44accepted challenger▼−1Since October 2026: 1% → 0%, −1 point. Inside the 11-point floor: within noise.1% → 0%08
dbt0%0%33accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
dbt0%0%33accepted 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.
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 six times of 52. Lab treatment is defined on the method page; the row is marked, not excluded.
For buyers
Head to headHead-to-head pages are published for mid-market buyers, so these open on mid-market figures, not enterprise.
All twenty-eight head-to-head pages: the top eight products, each against each
Hightouch vs AirbyteHightouch vs RudderStack Reverse ETLHightouch vs dbtHightouch vs FivetranBigQuery vs SnowflakeBigQuery vs CensusBigQuery vs AirbyteBigQuery vs RudderStack Reverse ETLBigQuery vs dbtBigQuery vs FivetranSnowflake vs CensusSnowflake vs AirbyteSnowflake vs RudderStack Reverse ETLSnowflake vs dbtSnowflake vs FivetranCensus vs AirbyteCensus vs RudderStack Reverse ETLCensus vs dbtCensus vs FivetranAirbyte vs RudderStack Reverse ETLAirbyte vs dbtAirbyte vs FivetranRudderStack Reverse ETL vs dbtRudderStack Reverse ETL vs Fivetrandbt vs Fivetran
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 →
010203040506070809101112Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative60%
Key
01Hightouch47%
Hightouch47%02Snowflake32%
Snowflake32%03Census10%
Census10%04BigQuery7%
BigQuery7%05Fivetran1%
Fivetran1%06Polytomic1%
Polytomic1%07Databricks SQL Warehouse0%
Databricks SQL Warehouse0%08dbt0%
dbt0%09RudderStack Reverse ETL0%
RudderStack Reverse ETL0%10Airbyte0%
Airbyte0%11Amazon Redshift0%
Amazon Redshift0%12Segment0%
Segment0%What they warned about
Nine of fourteen models held their first choice under the paraphrase. GPT-5.4 mini, Gemini 3.5 Flash, Mistral Small, 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.
Census19%
16 of 85 labels negative · 9 of 14 models · 5 hard negative
“Tools to Avoid or Approach with Caution ... Census (for Mid-Tier/Entry Plans) - Lacks enterprise SLAs at entry/mid-tier levels” MiniMax M2.5, negative prompt
Snowflake12%
9 of 76 labels negative · 9 of 14 models · 2 hard negative
“Avoid: Snowflake uses consumption-based pricing… Many companies report bills 200-300% higher than budgeted.” Muse Glimmer 30B, negative prompt
Amazon Redshift28%
9 of 32 labels negative · 7 of 14 models · 2 hard negative
“Avoid any warehouse that requires heavy cluster management (Redshift, ClickHouse, Azure Synapse)” DeepSeek V4 Flash, negative prompt
Segment39%
11 of 28 labels negative · 6 of 14 models · 5 hard negative
“Reverse ETL Tools to Avoid or Be Cautious About ... Segment got expensive after Twilio bought them” Claude Haiku 4.5, 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
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. 1116 links across 274 sites, every framing counted. Ranked by the number of answers carrying the site or page. 80 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.
vendor site · Hightouch44 answers · 102 citations · 12 models
vendor site · Funnel29 answers · 31 citations · 10 models
vendor site · Improvado27 answers · 38 citations · 11 models
vendor site · Skyvia26 answers · 37 citations · 10 models
26 answers · 29 citations · 10 models
25 answers · 25 citations · 11 models
vendor site · DataChannel21 answers · 33 citations · 8 models
vendor site · LeadJourney21 answers · 21 citations · 10 models
vendor site · RudderStack20 answers · 33 citations · 9 models
publisher (Gane)20 answers · 22 citations · 9 models
20 answers · 20 citations · 10 models
vendor site · Integrate19 answers · 34 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.
23 answers · 10 models
21 answers · 9 models
21 answers · 10 models
20 answers · 9 models
20 answers · 9 models
19 answers · 10 models
17 answers · 10 models
15 answers · 8 models
14 answers · 8 models
14 answers · 5 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 marketing data warehouse and reverse etl stack”, “marketing data warehouse and reverse etl stack”. 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 |
|---|---|---|---|---|---|---|---|---|
| Hightouch hightouch.com | 47% | 399 | 12,100 | 434 | 127,772 | 23 | ||
| Snowflake snowflake.com | 32% | 234 | 368,000 | 37,077 | 718,749 | 118 | ||
| Fivetran fivetran.com Census 10%, Fivetran 1% | 11% | 238 | 60,500 | 14,424 | 41,501 company | $126 | 97 | |
| Google cloud.google.com BigQuery 7% | 7% | 208 | 22,200 | 2,048 | 7,405,347 | |||
| Integrate.io integrate.io | 1% | 8 | 110 | 2 | 53,336 | 3 | 8 | |
| Omnata omnata.com | 1% | 13 | ||||||
| Polytomic polytomic.com | 1% | 59 | 590 | 16 | 882 | 1 | ||
| Databricks SQL Warehouse databricks.com | 0% | 64 | 260 | 32 | 689,756 | $34,664 | 120 | |
| dbt Labs getdbt.com dbt 0% | 0% | 122 | 75,753 | 12 | ||||
| RudderStack Reverse ETL rudderstack.com | 0% | 122 | 20 | 0 | 46,132 | 50 | 2 |
Google's top ten for the two searches hold 17 sites; 4 of them are among the sites the models cited here (improvado.io, integrate.io, rudderstack.com, skyvia.com). The first result for “best marketing data warehouse and reverse etl stack” is improvado.io.
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 marketing data warehouse and reverse ETL stack for an enterprise B2B company?”Paraphrase“Which reverse ETL and warehouse setup for a marketing team would you recommend to a large B2B company with thousands of employees?”Comparative“What are the top enterprise-grade data warehouse and reverse ETL tools for marketing teams and how do they differ?”Budget-constrained“What is the best marketing data warehouse and reverse ETL stack 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 marketing data warehouse and reverse ETL stack. What should we look at?”Negative“Which data warehouse and reverse ETL tools for marketing teams should a large enterprise avoid or be cautious about?”
Claude Haiku 4.5HightouchHightouchHeldCensus, HightouchFivetranagainst: HightouchCensus, Polytomicagainst: Amazon Redshift, BigQuery, Fivetran, Informatica, RudderStack Reverse ETL, Segment, Snowflake
Six alternatives
BigQuery, Census, GrowthLoop, Polytomic, RudderStack Reverse ETL, SnowflakeFour alternatives
BigQuery, Census, Fivetran, SnowflakeThree alternatives
GrowthLoop, Improvado, RudderStack Reverse ETLTwo alternatives
BigQuery, SnowflakeGPT-5.4 miniHightouch, SnowflakeHightouchChangedHightouch, SnowflakeBigQuery, HightouchHightouchagainst: Fivetran, Hightouch
Four alternatives
Census, Databricks SQL Warehouse, RudderStack Reverse ETL, dbtThree alternatives
BigQuery, Databricks SQL Warehouse, SnowflakeThree alternatives
BigQuery, Census, Databricks SQL WarehouseTwo alternatives
Databricks SQL Warehouse, SnowflakeFive alternatives
Airbyte, BigQuery, Fivetran, RudderStack Reverse ETL, SnowflakeGemini 3.5 FlashCensus, Hightouch, Snowflakeagainst: Segment, TealiumCensus, SnowflakeChangedagainst: Segment, TealiumHightouchBigQuery, Omnataagainst: SnowflakeCensus, Hightouch, Snowflakeagainst: DuckDB, Make, MongoDB, MySQL, Netezza, Oracle Autonomous Data Warehouse, SQL Server, SQLite, Teradata, Vanilla PostgreSQL, Workato, Zapier
Five alternatives
BigQuery, Fivetran, RudderStack Reverse ETL, Snowplow, dbtFour alternatives
BigQuery, Fivetran, Hightouch, dbtEight alternatives
Amazon Redshift, BigQuery, Census, Databricks SQL Warehouse, GrowthLoop, Omnata, RudderStack Reverse ETL, SnowflakeEight alternatives
AWS Redshift, Airbyte, Census, Cube.js, Fivetran, Hightouch, Microsoft Fabric, dbtFive alternatives
BigQuery, Databricks SQL Warehouse, Fivetran, Omnata, RudderStack Reverse ETLPerplexity SonarHightouch, SnowflakeHightouch, SnowflakeHeldHightouchBigQuery, Hightouch, Snowflakeno first choiceagainst: Adverity, Airbyte, Census, Funnel, Hevo, Multiwoven, Omnata, RudderStack Reverse ETL, Segment, Skyvia, Supermetrics
Four alternatives
BigQuery, Census, Fivetran, dbtTwo alternatives
Census, dbtEight alternatives
Amazon Redshift, BigQuery, Census, Databricks Lakehouse, DinMo, GrowthLoop, RudderStack Reverse ETL, SnowflakeFour alternatives
Adverity, Census, Funnel, dbtGrok 4.20Hightouch, Snowflakeagainst: Amazon RedshiftHightouch, SnowflakeHeldagainst: Grouparoo, Polytomic, RudderStack Reverse ETLHightouchagainst: Amazon Redshift, PanoplyHightouch, Snowflakeagainst: Census, Polytomic, RudderStack Reverse ETL, SegmentHightouch, Snowflakeagainst: Airbyte, Census, Hightouch, Omnata, Polytomic, Praxis Data, Segment, Skyvia
Seven alternatives
BigQuery, Census, Databricks SQL Warehouse, Microsoft Fabric, Polytomic, RudderStack Reverse ETL, dbtSix alternatives
Airbyte, BigQuery, Census, DataChannel, Fivetran, dbtFour alternatives
BigQuery, Census, RudderStack Reverse ETL, SnowflakeThree alternatives
BigQuery, Census, Databricks SQL WarehouseFour alternatives
BigQuery, Census, Databricks SQL Warehouse, FivetranMistral SmallHightouch, SnowflakeCensus, SnowflakeChangedAmazon Redshift, BigQuery, Census, Hightouch, SnowflakeHightouch, SnowflakeHightouch, Snowflakeagainst: Airbyte, Grouparoo, Polytomicagainst: Amazon Redshift, Census, Snowflake
Five alternatives
BigQuery, Census, LeadJourney, Segment, WorkatoFive alternatives
Airbyte, Databricks SQL Warehouse, Fivetran, Hightouch, dbtThree alternatives
Polytomic, RudderStack Reverse ETL, SegmentSeven alternatives
Airbyte, BigQuery, Census, Dataddo, Fivetran, Integrate.io, dbtThree alternatives
Amazon Redshift, BigQuery, CensusDeepSeek V4 FlashHightouch, Snowflakeagainst: Census, GrowthLoop, Polytomic, RudderStack Reverse ETL, SegmentHightouch, SnowflakeHeldagainst: CensusBigQuery, Hightouch, Snowflakeagainst: SegmentHightouch, Snowflakeagainst: AWS Redshift, Census, RudderStack Reverse ETL, SegmentCensus, Hightouchagainst: Amazon Redshift, Azure Synapse Analytics, Census, ClickHouse, Databand, Hevo, Segment, Snowflake, Tealium, mParticle
Four alternatives
BigQuery, Databricks SQL Warehouse, Fivetran, dbtOne alternative
Databricks SQL WarehouseEight alternatives
Amazon Redshift, Census, Databricks SQL Warehouse, Fivetran, Microsoft Azure Synapse Analytics, Microsoft Fabric, RudderStack Reverse ETL, dbtOne alternative
BigQueryOne alternative
RudderStack Reverse ETLLlama 4 MaverickHightouchHightouchHeldCensus, HightouchHightouchHightouchnothing named
Five alternatives
BigQuery, Databricks SQL Warehouse, LeadJourney, Snowflake, dbtTwo alternatives
Census, SnowflakeOne alternative
RudderStack Reverse ETLFour alternatives
BigQuery, Census, Snowflake, Windsor.aiFour alternatives
BigQuery, Databricks SQL Warehouse, Snowflake, dbtQwen 3.7 FlashHightouch, Snowflakeagainst: Airbyte, FivetronHightouch, SnowflakeHeldCensusHightouch, Snowflakeno first choiceagainst: Census, Datorama, Facebook Insights, Google Ads Data Hub, Grouparoo, Oracle Exadata, PostgreSQL, Supermetrics BI, Teradata
Three alternatives
Databricks SQL Warehouse, Starburst, dbtSix alternatives
Amazon Redshift, Census, Fivetran, Microsoft Azure Synapse Analytics, Microsoft Fabric, dbtSix alternatives
BigQuery, Databricks SQL Warehouse, Fivetran, Hightouch, Snowflake, Supermetrics Reverse ETLThree alternatives
RudderStack Reverse ETL, Segment, dbtKimi K2Hightouch, SnowflakeHightouch, SnowflakeHeldHightouch, SnowflakeBigQuery, Hightouchagainst: AWS Redshift, Census, Databricks SQL Warehouse, SnowflakeCensus, Hightouchagainst: Amazon Redshift, Polytomic, RudderStack Reverse ETLagainst: PostgreSQL, Stitch Data
Seven alternatives
Adobe Real-Time CDP B2B Edition, BigQuery, Census, Databricks SQL Warehouse, Demandbase, Fivetran, dbtTwo alternatives
Census, Databricks SQL WarehouseEight alternatives
Amazon Redshift, BigQuery, Census, Databricks SQL Warehouse, Microsoft Azure Synapse Analytics, Microsoft Fabric, RudderStack Reverse ETL, SegmentTwo alternatives
Databricks SQL Warehouse, SnowflakeGLM 4.7 FlashXHightouch, SnowflakeHightouch, SnowflakeHeldHightouch, SnowflakeBigQuery, Hightouchagainst: Amazon Redshift, Snowflakeno first choiceagainst: Delta, Looker, Microsoft Power BI, Segment, Tableau
Six alternatives
Amazon Redshift, BigQuery, Census, DataChannel, RudderStack Reverse ETL, dbtThree alternatives
Amazon Redshift, BigQuery, CensusThree alternatives
BigQuery, Census, Databricks SQL WarehouseMiniMax M2.5Hightouch, SnowflakeCensus, Hightouch, SnowflakeChangedHightouchIntegrate.io, Snowflakeagainst: BigQuery, Databricks SQL Warehouse, RudderStack Reverse ETLHightouch, Snowflakeagainst: Amazon Redshift, BigQuery, Census, Databricks SQL Warehouse, RudderStack Reverse ETL, Weldagainst: Amazon Redshift, Census, Snowflake
Nine alternatives
BigQuery, Census, Databricks SQL Warehouse, Fivetran, Freshpaint, Looker, Metabase, RudderStack Reverse ETL, dbtTwo alternatives
BigQuery, Databricks SQL WarehouseSix alternatives
Amazon Redshift, BigQuery, Census, RudderStack Reverse ETL, Segment, SnowflakeOne alternative
HightouchGPT-6 LunaHightouchHightouchHeldHightouchBigQueryCensus, Hightouchagainst: BigQuery, Census, Databricks SQL Warehouse, Hightouch, Snowflake
Six alternatives
BigQuery, Census, Databricks SQL Warehouse, Fivetran, Snowflake, dbtTwo alternatives
Snowflake, dbtTwo alternatives
Census, RudderStack Reverse ETLFour alternatives
Census, Hightouch, Snowflake, dbtTwo alternatives
Fivetran, dbtMuse Glimmer 30BBigQuery, Hightouch, SnowflakeHightouchChangedBigQuery, Hightouch, SnowflakeHightouch, Snowflakeagainst: CensusCensus, Hightouchagainst: Census, Snowflake
Five alternatives
Census, Fivetran, Improvado, LeadJourney, Windsor.aiThree alternatives
Census, Snowflake, dbtFour alternatives
Amazon Redshift, Census, RudderStack Reverse ETL, SegmentTwo alternatives
BigQuery, RudderStack Reverse ETLBold 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 08:38 | yes | 16 | 12 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 14:14 | yes | 6 | 7 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 14:46 | no | 0 | 18 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-11-01 14:39 | yes | 10 | 5 s |
| Direct recommendation | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 15:50 | yes | 14 | 16 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 10:36 | yes | 9 | 6 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 15:14 | yes | 24 | 40 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 16:51 | yes | 5 | 3 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 11:47 | no | 0 | 35 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 08:39 | yes | 25 | 34 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 13:39 | yes | 24 | 36 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 09:36 | no | 0 | 56 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-11-01 14:20 | yes | 4 | 24 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 11:07 | yes | 15 | 20 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 14:51 | yes | 27 | 13 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 10:59 | yes | 5 | 6 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 13:05 | no | 0 | 18 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-11-01 17:16 | yes | 10 | 6 s |
| Paraphrase | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 15:30 | yes | 15 | 13 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 12:18 | no | 0 | 8 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 11:14 | yes | 22 | 27 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 11:49 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 13:30 | yes | 15 | 44 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 17:34 | yes | 19 | 72 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 11:33 | yes | 24 | 184 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 09:17 | yes | 10 | 55 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-11-01 09:25 | yes | 4 | 14 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 08:34 | yes | 21 | 28 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 09:26 | yes | 28 | 16 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 09:37 | yes | 7 | 7 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 10:22 | yes | 11 | 26 s |
| Comparative | Perplexity Sonar | sonar | 2026-11-01 16:51 | yes | 10 | 9 s |
| Comparative | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 16:06 | yes | 15 | 44 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 15:23 | yes | 15 | 12 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 13:07 | yes | 25 | 53 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 12:12 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 10:55 | no | 0 | 30 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 10:32 | yes | 10 | 27 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 12:27 | yes | 23 | 58 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 08:38 | yes | 19 | 50 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-11-01 16:35 | yes | 9 | 26 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 15:00 | yes | 15 | 24 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 16:37 | yes | 28 | 14 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 13:22 | yes | 5 | 5 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 16:39 | no | 0 | 25 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-11-01 14:26 | yes | 10 | 5 s |
| Budget constrained | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 14:18 | yes | 5 | 12 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 15:18 | yes | 15 | 10 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 14:57 | yes | 23 | 25 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 16:57 | yes | 5 | 3 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 10:51 | yes | 10 | 64 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 17:24 | yes | 25 | 36 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 13:43 | yes | 25 | 91 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 16:44 | yes | 19 | 76 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-11-01 15:25 | yes | 6 | 33 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 17:35 | yes | 15 | 30 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 11:54 | yes | 27 | 16 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 17:01 | yes | 7 | 9 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 08:42 | no | 0 | 19 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-11-01 12:46 | yes | 10 | 12 s |
| Scale constrained | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 17:30 | yes | 10 | 17 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 11:08 | no | 0 | 9 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 14:29 | yes | 24 | 43 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 08:48 | yes | 5 | 3 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 14:30 | no | 0 | 36 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 09:48 | yes | 24 | 32 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 11:35 | yes | 24 | 53 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 12:25 | yes | 14 | 41 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-11-01 09:15 | yes | 5 | 29 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 15:45 | yes | 13 | 23 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 10:55 | yes | 37 | 18 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 12:42 | yes | 2 | 6 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 16:45 | no | 0 | 23 s |
| Negative framing | Perplexity Sonar | sonar | 2026-11-01 08:40 | yes | 10 | 6 s |
| Negative framing | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 17:22 | yes | 23 | 18 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 13:49 | yes | 19 | 9 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 16:46 | yes | 24 | 70 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 09:28 | yes | 10 | 4 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 08:53 | yes | 15 | 41 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 13:32 | yes | 21 | 29 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 16:32 | yes | 25 | 104 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 14:34 | yes | 25 | 60 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-11-01 11:16 | yes | 5 | 30 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 14:41 | yes | 25 | 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 Microsoft Azure Synapse Analytics
Databricks read as Databricks SQL Warehouse
Databricks (Lakehouse) read as Databricks SQL Warehouse
Databricks (with Delta Lake) read as Databricks SQL Warehouse
Databricks SQL read as Databricks SQL Warehouse
Oracle read as Oracle Autonomous Data Warehouse
RudderStack read as RudderStack Reverse ETL
Rudderstack read as RudderStack Reverse ETL
Unresolved, counted raw
Astera
Cube.js
Databand
Fivetron
Google BigQuery Omni
Microsoft Fabric Data Warehouse
Netezza
SQL Server
SQLite
Supermetrics BI
Supermetrics Reverse ETL
Twilio Segment Reverse ETL
Vanilla PostgreSQL
Discontinued, still offered
Grok 4.20 named Grouparoo as mention on the scale prompt. Open source reverse ETL, shut down 2023.