Data warehouse and reverse ETL for marketing
Asked as “marketing data warehouse and reverse ETL stack”, and as “reverse ETL and warehouse setup for a marketing team”, on behalf of a mid-market B2B company. 107 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
38%
Contested · BigQuery 21%
38Hightouch21BigQuery20Snowflake21others
38% of first choices, contested.
Since October 2026▼−2Since October 2026: 40% → 38%, −2 points. Inside the 11-point floor: within noise.Hightouch held the lead, −2 points on 40%, 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.This pageEnterpriseHightouch47%Clear leader▲+4Since October 2026: 43% → 47%, +4 points. Inside the 11-point floor: within noise.Standing →
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.This pageEnterpriseHightouch47%Clear leader▲+4Since October 2026: 43% → 47%, +4 points. Inside the 11-point floor: within noise.Standing →The standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all fourteen models, for a mid-market B2B company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince October 2026
01Hightouch38%13%78endorsed leader▼−2Since October 2026: 40% → 38%, −2 points. Inside the 11-point floor: within noise.40% → 38%
Hightouch38%13%78endorsed leader▼−2Since October 2026: 40% → 38%, −2 points. Inside the 11-point floor: within noise.40% → 38%02BigQuery Lab in the set21%8%75accepted challenger=heldSince October 2026: 21% → 21%, ±0 points. Inside the 11-point floor: within noise.21% → 21%
BigQuery Lab in the set21%8%75accepted challenger=heldSince October 2026: 21% → 21%, ±0 points. Inside the 11-point floor: within noise.21% → 21%03
Snowflake20%22%68accepted challenger▼−1Since October 2026: 21% → 20%, −1 point. Inside the 11-point floor: within noise.21% → 20%
Snowflake20%22%68accepted challenger▼−1Since October 2026: 21% → 20%, −1 point. Inside the 11-point floor: within noise.21% → 20%04
Census8%16%83accepted challenger▼−3Since October 2026: 11% → 8%, −3 points. Inside the 11-point floor: within noise.11% → 8%
Census8%16%83accepted challenger▼−3Since October 2026: 11% → 8%, −3 points. Inside the 11-point floor: within noise.11% → 8%05
Airbyte6%12%41accepted challenger▲+5Since October 2026: 1% → 6%, +5 points. Inside the 11-point floor: within noise.1% → 6%
Airbyte6%12%41accepted challenger▲+5Since October 2026: 1% → 6%, +5 points. Inside the 11-point floor: within noise.1% → 6%06
RudderStack Reverse ETL2%15%52accepted challenger=heldSince October 2026: 2% → 2%, ±0 points. Inside the 11-point floor: within noise.2% → 2%
RudderStack Reverse ETL2%15%52accepted challenger=heldSince October 2026: 2% → 2%, ±0 points. Inside the 11-point floor: within noise.2% → 2%07
dbt1%2%50accepted challenger▲+1Since October 2026: 0% → 1%, +1 point. Inside the 11-point floor: within noise.0% → 1%
dbt1%2%50accepted challenger▲+1Since October 2026: 0% → 1%, +1 point. Inside the 11-point floor: within noise.0% → 1%08
Fivetran1%26%31criticized challenger▲+1Since October 2026: 0% → 1%, +1 point. Inside the 11-point floor: within noise.0% → 1%
Fivetran1%26%31criticized challenger▲+1Since October 2026: 0% → 1%, +1 point. Inside the 11-point floor: within noise.0% → 1%Show the four products at 0%, ordered by negative rate
12
Databricks SQL Warehouse0%43%23criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
Databricks SQL Warehouse0%43%23criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%11
Segment0%34%29criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
Segment0%34%29criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%10
Amazon Redshift0%31%35criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
Amazon Redshift0%31%35criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%09
Polytomic0%9%22accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
Polytomic0%9%22accepted 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 twenty-one times of 52. Lab treatment is defined on the method page; the row is marked, not excluded.
For buyers
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% negative50%
Key
01Hightouch38%
Hightouch38%02BigQuery21%
BigQuery21%03Snowflake20%
Snowflake20%04Census8%
Census8%05Airbyte6%
Airbyte6%06RudderStack Reverse ETL2%
RudderStack Reverse ETL2%07dbt1%
dbt1%08Fivetran1%
Fivetran1%09Polytomic0%
Polytomic0%10Amazon Redshift0%
Amazon Redshift0%11Segment0%
Segment0%12Databricks SQL Warehouse0%
Databricks SQL Warehouse0%What they warned about
Four of fourteen models held their first choice under the paraphrase. GPT-5.4 mini, Gemini 3.5 Flash, Perplexity Sonar, Mistral Small, Llama 4 Maverick, Kimi K2, GLM 4.7 FlashX, MiniMax M2.5, GPT-6 Luna 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.
Census16%
13 of 83 labels negative · 11 of 14 models · 1 hard negative
“avoid Census post-acquisition pricing” DeepSeek V4 Flash, negative prompt
Snowflake22%
15 of 68 labels negative · 10 of 14 models
“Snowflake, BigQuery, Redshift, Databricks are excellent for analytics but: Data is only accessible to technical SQL users” Kimi K2, negative prompt
Hightouch13%
10 of 78 labels negative · 8 of 14 models · 1 hard negative
“avoid Hightouch if you lack SQL expertise” DeepSeek V4 Flash, negative prompt
Segment34%
10 of 29 labels negative · 8 of 14 models · 1 hard negative
“Avoid bundled CDPs (Segment, Tealium) if you want warehouse-first architecture” Kimi K2, scale 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. 1037 links across 245 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.
34 answers · 40 citations · 11 models
vendor site · Skyvia33 answers · 40 citations · 11 models
vendor site · DataChannel28 answers · 44 citations · 9 models
vendor site · Hightouch26 answers · 49 citations · 12 models
vendor site · Improvado26 answers · 33 citations · 10 models
21 answers · 23 citations · 8 models
vendor site · LeadJourney21 answers · 21 citations · 10 models
publisher (Gane)20 answers · 30 citations · 9 models
19 answers · 20 citations · 8 models
vendor site · Porter Metrics16 answers · 19 citations · 8 models
vendor site · Funnel16 answers · 18 citations · 11 models
16 answers · 16 citations · 9 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.
21 answers · 8 models
21 answers · 10 models
20 answers · 10 models
20 answers · 8 models
19 answers · 9 models
19 answers · 8 models
19 answers · 9 models
16 answers · 9 models
16 answers · 9 models
16 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 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 | 38% | 399 | 12,100 | 434 | 127,772 | 23 | ||
| Google cloud.google.com BigQuery 21%, Looker 0%, Looker Studio 0% | 21% | 208 | 40,500 | 452 | 7,405,347 | |||
| Snowflake snowflake.com | 20% | 234 | 368,000 | 37,077 | 718,749 | 118 | ||
| Fivetran fivetran.com Census 8%, Fivetran 1% | 9% | 238 | 60,500 | 14,424 | 41,501 company | $126 | 97 | |
| Airbyte airbyte.com | 6% | 105 | 6,600 | 120 | 17,507 | $320 | 42 | |
| RudderStack Reverse ETL rudderstack.com | 2% | 122 | 20 | 0 | 46,132 | 50 | 2 | |
| Skyvia skyvia.com | 2% | 20 | 1,300 | 15 | 33,150 | 1 | 7 | |
| dbt Labs getdbt.com dbt 1% | 1% | 122 | 75,753 | 12 | ||||
| PostgreSQL postgresql.org | 1% | 27 | 74,000 | 14,143 | 465,585 | |||
| Multiwoven multiwoven.com | 1% | 5 |
Google's top ten for the two searches hold 17 sites; 3 of them are among the sites the models cited here (astera.com, improvado.io, 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 a mid-market B2B company?”Paraphrase“Which reverse ETL and warehouse setup for a marketing team would you recommend to a mid-sized B2B company?”Comparative“What are the top 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 company with a limited budget?”Scale-constrained“We are a 500 person company 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 I avoid or be cautious about?”
Claude Haiku 4.5HightouchHightouchHeldBigQuery, HightouchBigQuery, SkyviaCensus, Hightouchagainst: Fivetran, Meltano, Polytomic, RudderStack Reverse ETL, Segment
Seven alternatives
Amazon Redshift, BigQuery, Census, Hevo, Improvado, Polytomic, SnowflakeFive alternatives
Airbyte, BigQuery, Census, Snowflake, dbtFour alternatives
Amazon Redshift, Census, RudderStack Reverse ETL, SnowflakeThree alternatives
Firebolt, MotherDuck, RudderStack Reverse ETLThree alternatives
Fivetran, Mozart Data, PolytomicGPT-5.4 miniHightouch, Snowflakeagainst: SegmentBigQuery, Hightouch, SnowflakeChangedHightouchAirbyte, BigQueryagainst: Census, Hightouch, SnowflakeCensus, Hightouchagainst: Amazon Redshift, BigQuery, Fivetran, Hightouch, Segment, Snowflake
Three alternatives
BigQuery, Hightouch Composable CDP, dbtThree alternatives
Census, Fivetran, dbtFour alternatives
BigQuery, Census, RudderStack Reverse ETL, SnowflakeTwo alternatives
Airbyte Data Activation, dbtSix alternatives
Amazon Redshift, BigQuery, RudderStack Reverse ETL, Segment, Snowflake, dbtGemini 3.5 FlashHightouch, SnowflakeCensus, Hightouch, SnowflakeChangedagainst: Salesforce Data Cloud, SegmentBigQuery, Census, HightouchBigQuery, Hightouchagainst: Amazon Redshift, SnowflakeHightouchagainst: Segment, Tealiumagainst: AWS Redshift, ClickHouse, Databricks SQL Warehouse, Make, MySQL, Postgres on AWS RDS, Workato, Zapier
Four alternatives
BigQuery, Census, Fivetran, dbtThree alternatives
BigQuery, Fivetran, dbtFour alternatives
Databricks SQL Warehouse, Polytomic, RudderStack Reverse ETL, SnowflakeFour alternatives
Census, GA4 Native Export + Airbyte, Meltano, dbtSeven alternatives
BigQuery, Census, Fivetran, RudderStack Reverse ETL, Snowflake, Supermetrics, dbtPerplexity SonarBigQuery, Hightouch, SnowflakeHightouch, SnowflakeChangedHightouchBigQueryagainst: Census, Hightouchno first choiceagainst: Airbyte, Boomi, Fivetran, Hevo, Multiwoven, Omnata, RudderStack Reverse ETL, Segment
Eight alternatives
Airbyte, Census, Fivetran, Improvado, Omnata, RudderStack Reverse ETL, Segment, dbtFive alternatives
Airbyte, BigQuery, Census, Fivetran, dbtNine alternatives
Amazon Redshift, BigQuery, Census, Databricks SQL Warehouse, DinMo, Improvado, RudderStack Reverse ETL, Segment, SnowflakeSix alternatives
Airbyte, Census, Metabase, RudderStack Reverse ETL, Skyvia, dbtGrok 4.20BigQuery, HightouchBigQuery, HightouchHeldagainst: Airbyte, Amazon Redshift, Databricks SQL Warehouse, PostgreSQLBigQuery, HightouchAirbyte, Multiwoven, PostgreSQL, dbtagainst: Census, Fivetran, Grouparoo, Hightouch, SnowflakeHightouch, Snowflakeagainst: Amazon Redshift, Databricks SQL Warehouse, RudderStack Reverse ETL, Segment, mParticleagainst: Amazon Redshift, Census, Databricks SQL Warehouse, Grouparoo, Hevo, Hightouch, PostgreSQL, RudderStack Reverse ETL, Snowflake, dbt
Five alternatives
Airbyte, Census, Fivetran, Snowflake, dbtFour alternatives
Census, Polytomic, RudderStack Reverse ETL, SnowflakeFour alternatives
Amazon Redshift, Census, RudderStack Reverse ETL, SnowflakeTen alternatives
Apache Airflow, BigQuery, Dagster, DuckDB, Lightdash, Meltano, Metabase, Polytomic, RudderStack Reverse ETL, SupabaseSeven alternatives
Airbyte, BigQuery, Census, Fivetran, Improvado, Windsor.ai, dbtMistral SmallHightouch, SnowflakeCensus, SnowflakeChangedAmazon Redshift, BigQuery, Census, Hightouch, SnowflakeAirbyte, BigQueryCensus, Hightouch, Snowflakeagainst: Databricks SQL Warehouse, Pipedreamagainst: Airbyte, Amazon Redshift, Azure Synapse Analytics, Fivetran, IBM Netezza, Make, Oracle Exadata, Peliqan, Polytomic, Teradata, Workato, Zapier
Three alternatives
BigQuery, Census, dbtSeven alternatives
Airbyte, BigQuery, Fivetran, Hightouch, RudderStack Reverse ETL, Segment, dbtTwo alternatives
DataChannel, dbtThree alternatives
DataChannel, RudderStack Reverse ETL, dbtFive alternatives
Airbyte, Amazon Redshift, BigQuery, Grouparoo, PostgreSQLDeepSeek V4 FlashBigQuery, Hightouchagainst: Amazon RedshiftBigQuery, HightouchHeldagainst: Amazon RedshiftBigQuery, HightouchAirbyte, BigQuery, Hightouchagainst: Fivetran, Funnel, Snowflake, SupermetricsCensus, Hightouchagainst: RudderStack Reverse ETLagainst: Amazon Redshift, Census, Hightouch, Integrate.io, Microsoft Azure Synapse Analytics, Oracle Exadata, RudderStack Reverse ETL, Teradata
Eight alternatives
Airbyte, Census, Dreamdata, Fivetran, HockeyStack, Looker Studio, Snowflake, dbtSix alternatives
Airbyte, Census, Fivetran, RudderStack Reverse ETL, Snowflake, dbtEight alternatives
Airbyte, Amazon Redshift, Census, Databricks SQL Warehouse, Dataddo, Polytomic, RudderStack Reverse ETL, SnowflakeFive alternatives
Looker Studio, Metabase, RudderStack Reverse ETL, Windsor.ai, dbtFour alternatives
BigQuery, GrowthLoop, Segment, SnowflakeLlama 4 MaverickHightouchCensus, Hightouch, RudderStack Reverse ETLChangedno first choiceno first choiceRudderStack Reverse ETLagainst: Census, Fivetran
Four alternatives
BigQuery, Census, Snowflake, dbtTwo alternatives
BigQuery, SnowflakeSix alternatives
BigQuery, Census, Hightouch, Improvado, Snowflake, Windsor.aiThree alternatives
Fivetran, Twilio, dbt LabsQwen 3.7 FlashHightouch, SnowflakeHightouch, SnowflakeHeldHightouch, SnowflakeBigQuery, Skyviaagainst: Fullstory, Polyconseil, Segment, SnowflakeFivetranagainst: Airbyteagainst: Airbyte, BigQuery, Castled, Census, Databricks SQL Warehouse, Grouparoo, Hightouch, Snowflake
Four alternatives
Airbyte, BigQuery, Fivetran, RudderStack Reverse ETLThree alternatives
BigQuery, Census, dbtFour alternatives
Amazon Redshift, BigQuery, Census, RudderStack Reverse ETLSeven alternatives
Airbyte, Databricks SQL Warehouse, DuckDB, Hightouch, Multiwoven, Windsor.ai, dbtOne alternative
CensusKimi K2BigQuery, Hightouch, SnowflakeHightouch, SnowflakeChangedagainst: Databricks SQL WarehouseHightouchAirbyte, BigQueryagainst: SnowflakeHightouch, Snowflakeagainst: Segment, Tealiumagainst: Amazon Redshift, BigQuery, Census, Databricks SQL Warehouse, Hightouch, Matillion, Snowflake
Four alternatives
Airbyte, Census, Fivetran, dbtFive alternatives
BigQuery, Census, Hevo, Improvado, RudderStack Reverse ETLSeven alternatives
Airbyte, Amazon Redshift, BigQuery, Census, Polytomic, RudderStack Reverse ETL, SnowflakeFour alternatives
DuckDB, Hightouch, MotherDuck, RudderStack Reverse ETLFour alternatives
Airbyte, BigQuery, Census, FivetranGLM 4.7 FlashXBigQuery, Hightouchagainst: SnowflakeHightouch, SnowflakeChangedHightouchAirbyte, BigQuery, Hightouchagainst: Census, SnowflakeCensus, Hightouch, Snowflakeagainst: Adobe Experience Cloud, Salesforce Data Cloud, Segmentnothing named
Four alternatives
Airbyte, Census, RudderStack Reverse ETL, dbtOne alternative
dbtFour alternatives
Amazon Redshift, BigQuery, Census, SnowflakeThree alternatives
PostgreSQL, Windsor.ai, dbtThree alternatives
BigQuery, Databricks SQL Warehouse, dbtMiniMax M2.5BigQuery, Hightouch, SnowflakeHightouch, SnowflakeChangedBigQuery, HightouchBigQuery, Hightouchno first choiceagainst: Amazon Redshift, BigQuery, Census, Fivetran, Hightouch, RudderStack Reverse ETL, Snowflake
Two alternatives
Census, dbtFour alternatives
Amazon Redshift, BigQuery, Census, PolytomicFour alternatives
Amazon Redshift, Census, RudderStack Reverse ETL, SnowflakeFour alternatives
PostgreSQL, RudderStack Reverse ETL, Snowflake, dbtGPT-6 LunaBigQuery, SnowflakeHightouchChangedHightouchagainst: Databricks SQL WarehouseBigQueryCensus, Hightouchagainst: Censusagainst: BigQuery, Census, Hightouch, Snowflake
Four alternatives
Census, Fivetran, Hightouch, dbtFour alternatives
BigQuery, Census, Snowflake, dbtFive alternatives
Amazon Redshift, BigQuery, Census, Segment Reverse ETL, SnowflakeFour alternatives
Airbyte, Hightouch, RudderStack Reverse ETL, dbtOne alternative
RudderStack Reverse ETLMuse Glimmer 30BHightouchHightouch, SnowflakeChangedagainst: RudderStack Reverse ETLHightouchBigQuery, HightouchHightouchagainst: BigQuery, Census, Databricks SQL Warehouse, Grouparoo, Hevo, Snowflake
Three alternatives
Census, RudderStack Reverse ETL, dbtTwo alternatives
BigQuery, CensusOne alternative
CensusEight alternatives
Airbyte, GitHub Multiwoven, Grouparoo, Jitsu, PostgreSQL, RudderStack Reverse ETL, Skyvia, dbtTwo alternatives
Census, 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 09:40 | yes | 16 | 12 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 10:19 | yes | 5 | 5 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 11:19 | no | 0 | 15 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-11-01 15:47 | yes | 10 | 7 s |
| Direct recommendation | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 16:38 | yes | 14 | 14 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 17:21 | yes | 10 | 7 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 15:29 | yes | 25 | 44 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 08:37 | yes | 5 | 3 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 09:42 | yes | 5 | 35 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 15:54 | yes | 23 | 34 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 13:12 | yes | 24 | 147 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 13:43 | yes | 5 | 17 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-11-01 08:34 | yes | 5 | 22 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 17:21 | yes | 23 | 35 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 09:46 | yes | 19 | 12 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 13:31 | no | 0 | 4 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 10:22 | no | 0 | 18 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-11-01 12:48 | yes | 10 | 6 s |
| Paraphrase | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 14:14 | yes | 10 | 13 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 15:54 | no | 0 | 5 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 10:46 | yes | 25 | 30 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 14:28 | yes | 5 | 3 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 15:15 | yes | 10 | 34 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 12:40 | yes | 19 | 77 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 15:00 | yes | 15 | 67 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 10:33 | yes | 19 | 33 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-11-01 14:02 | yes | 6 | 27 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 08:38 | yes | 14 | 21 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 15:55 | yes | 24 | 17 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 17:01 | yes | 8 | 9 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 13:48 | no | 0 | 17 s |
| Comparative | Perplexity Sonar | sonar | 2026-11-01 16:06 | yes | 10 | 9 s |
| Comparative | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 17:27 | yes | 15 | 14 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 13:08 | yes | 10 | 10 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 16:07 | yes | 24 | 58 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 13:55 | yes | 10 | 4 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 14:25 | yes | 20 | 26 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 17:17 | yes | 14 | 33 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 11:48 | yes | 23 | 51 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 09:50 | yes | 19 | 37 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-11-01 13:56 | yes | 8 | 21 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 10:49 | yes | 15 | 21 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 11:55 | yes | 19 | 10 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 09:02 | yes | 2 | 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 08:56 | yes | 10 | 21 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-11-01 17:32 | yes | 10 | 7 s |
| Budget constrained | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 14:35 | yes | 5 | 11 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 09:02 | yes | 10 | 6 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 13:28 | yes | 25 | 29 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 12:53 | yes | 5 | 3 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 13:29 | yes | 15 | 35 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 14:31 | yes | 20 | 41 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 13:29 | yes | 25 | 37 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 15:14 | no | 0 | 17 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-11-01 12:54 | yes | 5 | 20 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 12:16 | yes | 12 | 19 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 11:58 | yes | 16 | 17 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 14:03 | no | 0 | 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 16:13 | no | 0 | 20 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-11-01 09:51 | yes | 10 | 8 s |
| Scale constrained | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 17:22 | yes | 5 | 13 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 10:37 | no | 0 | 9 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 15:42 | yes | 24 | 54 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 10:34 | yes | 5 | 3 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 11:26 | no | 0 | 32 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 17:15 | yes | 25 | 42 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 13:59 | yes | 25 | 48 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 16:43 | no | 0 | 21 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-11-01 12:15 | yes | 3 | 25 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 13:37 | yes | 15 | 28 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 13:26 | yes | 15 | 10 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 11:35 | yes | 5 | 8 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 15:42 | yes | 1 | 27 s |
| Negative framing | Perplexity Sonar | sonar | 2026-11-01 17:16 | yes | 10 | 6 s |
| Negative framing | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 14:12 | yes | 15 | 21 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 10:17 | yes | 19 | 12 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 15:54 | yes | 25 | 47 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 13:45 | yes | 9 | 5 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 15:05 | yes | 25 | 47 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 14:02 | yes | 25 | 30 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 14:56 | yes | 23 | 107 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 08:45 | yes | 24 | 48 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-11-01 15:06 | yes | 4 | 26 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 09:42 | yes | 24 | 35 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 SQL read as Databricks SQL Warehouse
RudderStack read as RudderStack Reverse ETL
Rudderstack read as RudderStack Reverse ETL
Unresolved, counted raw
Airbyte Data Activation
Castled
Circly
Clarisights
Dataform
Deepnote
Fivetran Free Tier
Fivetran-managed warehouse stack
Funnel IO
GA4 Native Export + Airbyte
GitHub Multiwoven
Hightouch Composable CDP
IBM Netezza
Polyconseil
Postgres on AWS RDS
Segment Personas
Twilio
Windsor AI
dbt Labs
dbt Metrics
Discontinued, still offered
Muse Glimmer 30B named Grouparoo as alternative on the budget prompt. Open source reverse ETL, shut down 2023.
MiniMax M2.5 named Grouparoo as mention on the scale prompt. Open source reverse ETL, shut down 2023.
Mistral Small named Grouparoo as alternative on the scale prompt. Open source reverse ETL, shut down 2023.