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. 81 first choices recorded across the direct, paraphrase, budget and scale prompts, twelve models each.
Standing · first-choice share
44%
Clear leader
44Hightouch30Snowflake11BigQuery15others
44% of first choices, clear leader.
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.
The standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all twelve models, for an enterprise B2B company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrant
Show the seven products at 0%, ordered by negative rate
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 two times of 4; the other eleven models seven times of 44. Lab treatment is defined on the method page; the row is marked, not excluded.
Head to headHead-to-head pages are published for mid-market buyers, so these open on mid-market figures, not enterprise.
All fifteen head-to-head pages: the top six products, each against each
Hightouch vs RudderStack Reverse ETLHightouch vs PolytomicBigQuery vs SnowflakeBigQuery vs CensusBigQuery vs RudderStack Reverse ETLBigQuery vs PolytomicSnowflake vs CensusSnowflake vs RudderStack Reverse ETLSnowflake vs PolytomicCensus vs RudderStack Reverse ETLCensus vs PolytomicRudderStack Reverse ETL vs Polytomic
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 →
01
02
03
04
05
06
07
08
09
10
11
12
13Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative60%
Key
01Hightouch44%
Hightouch44%02Snowflake30%
Snowflake30%03BigQuery11%
BigQuery11%04Census10%
Census10%05Airbyte1%
Airbyte1%06Improvado1%
Improvado1%07Fivetran0%
Fivetran0%08dbt0%
dbt0%09RudderStack Reverse ETL0%
RudderStack Reverse ETL0%10Databricks SQL Warehouse0%
Databricks SQL Warehouse0%11Amazon Redshift0%
Amazon Redshift0%12Polytomic0%
Polytomic0%13Segment0%
Segment0%What they warned about
Five of twelve models held their first choice under the paraphrase. Claude Haiku 4.5, Gemini 3.5 Flash, Perplexity Sonar, Mistral Small, Qwen 3.7 Flash, GLM 4.7 FlashX and MiniMax M2.5 changed. A high negative share on a product with few labels is a warning. A low share on a product with many labels is salience, not sentiment.
Census17%
11 of 66 labels negative · 7 of 12 models · 2 hard negative
“The biggest "avoid/thoroughly vet" call here is Census/Fivetran Activations” DeepSeek V4 Flash, negative prompt
Amazon Redshift31%
10 of 32 labels negative · 6 of 12 models
“requires significant data engineering... No built-in attribution model, no CAPI activation. (referring to general-purpose warehouses like BigQuery/Redshift)” Claude Haiku 4.5, negative prompt
Hightouch10%
7 of 67 labels negative · 6 of 12 models
“Both Census and Hightouch charge based on active segments/users. For "thousands of users," standard pricing would bankrupt you.” Qwen 3.7 Flash, budget prompt
Teradata71%
5 of 7 labels negative · 5 of 12 models · 4 hard negative
“Avoid: On-Premises / Legacy Enterprise Data Warehouses (e.g., legacy Oracle, Teradata, IBM Db2)” Gemini 3.5 Flash, negative prompt
What they cite
Four of the twelve models returned a source list in this edition: four return the pages they cited.
Sites the answers cite
23 of 72 answers in this category came back with a source list, from 4 of 12 models: citations where the model returns them, or the search results it consulted. 361 links across 137 sites, every framing counted. Ranked by the number of answers carrying the site or page. The other 8 models searched through a gateway that returned no source list on this edition.
vendor site · Improvado15 answers · 34 citations · 3 models
vendor site · Hightouch11 answers · 23 citations · 4 models
vendor site · Domo11 answers · 14 citations · 3 models
10 answers · 10 citations · 3 models
vendor site · Cometly8 answers · 22 citations · 3 models
vendor site · Skyvia8 answers · 9 citations · 3 models
7 answers · 7 citations · 3 models
vendor site · Funnel6 answers · 11 citations · 2 models
vendor site · Integrate6 answers · 9 citations · 2 models
vendor site · Fivetran6 answers · 8 citations · 3 models
vendor site · LeadJourney6 answers · 7 citations · 2 models
vendor site · Fastero6 answers · 6 citations · 3 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.
11 answers · 3 models
11 answers · 3 models
10 answers · 3 models
7 answers · 2 models
6 answers · 3 models
6 answers · 2 models
6 answers · 2 models
5 answers · 3 models
5 answers · 3 models
5 answers · 2 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 | 44% | 399 | 12,100 | 434 | 127,772 | 23 | ||
| Snowflake snowflake.com | 30% | 234 | 368,000 | 37,077 | 718,749 | 118 | ||
| Google cloud.google.com BigQuery 11%, Looker 0% | 11% | 208 | 22,200 | 2,048 | 7,405,347 | |||
| Fivetran fivetran.com Census 10%, Fivetran 0% | 10% | 238 | 60,500 | 14,424 | 41,501 company | $126 | 97 | |
| Airbyte airbyte.com | 1% | 105 | 6,600 | 120 | 17,507 | $320 | 42 | |
| Improvado improvado.io | 1% | 33 | 880 | 2 | 85,809 | 6 | 1 | |
| Weld weld.app | 1% | 7 | 165,000 | 152,391 | 30,335 | 0 | ||
| Omnata omnata.com | 1% | 13 | ||||||
| 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; 5 of them are among the sites the models cited here (domo.com, getbruin.com, improvado.io, integrate.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 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 4.5BigQuery, Hightouch, SnowflakeHightouchChangedHightouchBigQuery, Hightouchagainst: Fivetran, Snowflakeno first choiceagainst: Amazon Redshift, BigQuery, Segment
Five alternatives
Census, Fivetran, LeadJourney, Polytomic, RudderStack Reverse ETLThree alternatives
Census, GrowthLoop, RudderStack Reverse ETLFour alternatives
Census, Fivetran, Salesforce Data Cloud, SegmentTwo alternatives
Amazon Redshift, CensusThree alternatives
Census, Fivetran, HightouchGPT-5.4 miniHightouch, SnowflakeHightouch, SnowflakeHeldHightouch, Snowflakeagainst: WorkatoHightouch, Snowflakeagainst: BigQueryHightouchnothing named
Six alternatives
Apache Airflow, BigQuery, Census, Databricks SQL Warehouse, RudderStack Reverse ETL, dbtFour alternatives
BigQuery, Census, Databricks SQL Warehouse, dbtFive alternatives
Amazon Redshift, BigQuery, Census, Databricks Lakehouse, Salesforce Data CloudOne alternative
CensusThree alternatives
RudderStack Reverse ETL, Twilio Segment / Engage, mParticle Warehouse SyncGemini 3.5 FlashHightouch, Snowflakeagainst: Segment, TealiumHightouchChangedagainst: Adobe Real-Time CDP, SalesforceBigQuery, Census, Hightouch, SnowflakeBigQuery, Hightouch, Omnataagainst: Census, SnowflakeBigQuery, Snowflakeagainst: Apache Druid, Boomi, ClickHouse, IBM Db2, MuleSoft, MySQL, Oracle Autonomous Data Warehouse, PostgreSQL, SQL Server, Segment, Teradata, Workato, Zapier, mParticle
Five alternatives
Airbyte, BigQuery, Census, Fivetran, dbtFour alternatives
BigQuery, Census, Snowflake, dbtThree alternatives
Amazon Redshift, Databricks SQL Warehouse, RudderStack Reverse ETLSix alternatives
Airbyte, Amazon Redshift, Fivetran, Looker, Microsoft Power BI, MultiwovenTwo alternatives
Census, HightouchPerplexity SonarSnowflakeHightouchChangedagainst: PolytomicCensus, Hightouch, SnowflakeBigQuery, Census, Hightouchagainst: Tableauno first choiceagainst: AWS Glue, Airbyte, Amazon Redshift, ClickHouse, Databricks SQL Warehouse, Fivetran, Microsoft Azure Synapse Analytics, Stitch
Four alternatives
BigQuery, Census, Hightouch, ImprovadoThree alternatives
BigQuery, Census, SnowflakeFour alternatives
Amazon Redshift, BigQuery, Microsoft Azure Synapse Analytics, WeldTwo alternatives
Snowflake, dbtGrok 4.20Hightouch, Snowflakeagainst: SegmentHightouch, SnowflakeHeldHightouch, Snowflakeagainst: Databricks SQL WarehouseCensus, Hightouch, Snowflakeagainst: Amazon Redshift, BigQueryCensus, Snowflakeagainst: Amazon Redshift, BigQuery, Census, Hightouch, Polytomic, Segement/RudderStack, Teradata, Zapier
Four alternatives
BigQuery, Census, Polytomic, dbtFour alternatives
BigQuery, Census, Databricks SQL Warehouse, FivetranFour alternatives
Amazon Redshift, BigQuery, Census, FivetranOne alternative
ImprovadoFour alternatives
BigQuery, Databricks SQL Warehouse, Hightouch, RudderStack Reverse ETLMistral SmallHightouch, SnowflakeHightouchChangedHightouch, SnowflakeBigQuery, Hightouchagainst: WeldHightouch, Snowflakeagainst: Census, ClickHouse, Grouparoo, Hightouch, IBM Db2 Warehouse, MotherDuck, Omnata, Oracle Autonomous Data Warehouse, Original Amazon Redshift, Polytomic, Teradata, Vertica
Thirteen alternatives
Airbyte, Alation, BigQuery, Census, Collibra, Databricks SQL Warehouse, Fivetran, Great Expectations, Monte Carlo, RudderStack Reverse ETL, Segment, Soda, dbtSeven alternatives
Airbyte, Amazon Redshift, BigQuery, Census, Fivetran, Snowflake, dbtEight alternatives
Amazon Redshift, Azure Synapse Analytics, BigQuery, Census, Fivetran, Improvado, RudderStack Reverse ETL, dbtFour alternatives
Census, Fivetran, Snowflake, dbtSeven alternatives
Airbyte, Amazon Redshift, BigQuery, Census, Fivetran, Segment Reverse ETL, Stitch DataDeepSeek V4 FlashHightouch, Snowflakeagainst: Databricks SQL WarehouseHightouch, SnowflakeHeldagainst: Databricks SQL Warehouse, PolytomicDatabricks SQL Warehouse, Hightouch, Snowflakeagainst: Adobe Real-Time CDP, Segment, TealiumBigQuery, Hightouchagainst: Amazon Redshift, Census, Integrate.io, Segment, SnowflakeCensus, Hightouchagainst: Amazon Redshift, Databricks SQL Warehouseagainst: Amazon Redshift, Census, Hightouch, IBM, Informatica PowerCenter, Oracle Exadata, RudderStack Reverse ETL, Teradata
Seven alternatives
Airbyte, BigQuery, Census, Fivetran, Polytomic, RudderStack Reverse ETL, dbtSix alternatives
Airbyte, BigQuery, Census, Fivetran, RudderStack Reverse ETL, dbtFive alternatives
Amazon Redshift, BigQuery, Census, Fivetran, RudderStack Reverse ETLOne alternative
FivetranThree alternatives
Fivetran, Polytomic, RudderStack Reverse ETLLlama 4 Maverickno first choiceno first choiceHeldHightouchHightouchno first choicenothing named
Five alternatives
Census, Domo, Fivetran, RudderStack Reverse ETL, SkyviaThree alternatives
Census, Fivetran, PolytomicQwen 3.7 FlashCensus, Hightouch, SnowflakeHightouchChangedBigQuery, Census, Hightouch, SnowflakeAirbyte, BigQueryagainst: Census, HightouchCensus, Hightouchagainst: Census, RudderStack Reverse ETL
Two alternatives
Fivetran, dbtThree alternatives
Fivetran, Snowflake, dbtFive alternatives
Amazon Redshift, Fivetran, Improvado, Polytomic, dbtThree alternatives
Databricks SQL Warehouse, Fivetran, SnowflakeSeven alternatives
BigQuery, Databricks SQL Warehouse, RudderStack Reverse ETL, Segment, Snowflake, dbt, mParticleKimi K2Hightouch, SnowflakeHightouch, SnowflakeHeldagainst: Adobe Real-Time CDP, SegmentHightouch, Snowflakeagainst: Amazon Redshift, FivetranHightouch, Snowflakeagainst: BigQuery, Census, Databricks SQL Warehouse, Segment, mParticleCensus, Snowflakeagainst: Segmentagainst: Adobe Real-Time CDP, Amazon Redshift, Azure Synapse Analytics, Census, Hightouch, IBM Db2, Oracle Autonomous Data Warehouse, Polytomic, Responsys, RudderStack Reverse ETL, Salesforce Marketing Cloud, Teradata
Seven alternatives
Airbyte, BigQuery, Census, Databricks SQL Warehouse, Fivetran, RudderStack Reverse ETL, dbtSix alternatives
Airbyte, BigQuery, Census, Databricks SQL Warehouse, Fivetran, dbtFour alternatives
BigQuery, Census, Databricks SQL Warehouse, ImprovadoThree alternatives
Fivetran, RudderStack Reverse ETL, Tealium Data CloudFive alternatives
BigQuery, Databricks SQL Warehouse, Hightouch, RudderStack Reverse ETL, dbtGLM 4.7 FlashXBigQuery, Census, Hightouch, SnowflakeHightouch, SnowflakeChangedBigQuery, HightouchWeldagainst: Amazon RedshiftHightouch, Snowflakeagainst: Looker Studio
Five alternatives
Airbyte, Amazon Redshift, Fivetran, Improvado, dbtThree alternatives
Census, Fivetran, dbtSeven alternatives
Amazon Redshift, Azure Synapse Analytics, Census, Fivetran, Improvado, RudderStack Reverse ETL, SnowflakeThree alternatives
BigQuery, Census, SnowflakeFour alternatives
Amazon Redshift, BigQuery, Census, FivetranMiniMax M2.5Hightouch, SnowflakeHightouchChangedCensus, HightouchImprovadoagainst: Census, Fivetran, Hightouch, dbtHightouchagainst: Census, Hightouch
Four alternatives
Amazon Redshift, BigQuery, Census, DomoFour alternatives
BigQuery, Census, Snowflake, dbtFour alternatives
Fivetran, Improvado, RudderStack Reverse ETL, SnowflakeTwo alternatives
Snowflake, WeldTwo alternatives
Census, Integrate.ioBold 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.
Seventy-two 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 | 2026-09-15 00:37 | yes | 13 | 11 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-09-15 00:29 | yes | 8 | 7 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-09-15 03:05 | yes | 15 | 28 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-09-15 02:44 | yes | 20 | 6 s |
| Direct recommendation | Grok 4.20 | spacexai/grok-4.1-fast-non-reasoning via vertex (asked for grok-4.20-non-reasoning; the API answered as this version) | 2026-09-15 04:33 | yes | 0 | 10 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-09-14 23:12 | yes | 0 | 11 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via fireworks | 2026-09-15 02:48 | yes | 0 | 25 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-09-15 03:15 | yes | 0 | 2 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-09-14 23:17 | no | 0 | 29 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-09-15 02:08 | yes | 0 | 50 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-09-14 23:32 | yes | 0 | 344 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-09-15 00:57 | yes | 0 | 20 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-09-15 02:30 | yes | 16 | 10 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-09-15 01:37 | yes | 7 | 6 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-09-15 04:39 | yes | 18 | 28 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-09-15 00:56 | yes | 15 | 8 s |
| Paraphrase | Grok 4.20 | spacexai/grok-4.1-fast-non-reasoning via vertex (asked for grok-4.20-non-reasoning; the API answered as this version) | 2026-09-14 23:40 | yes | 0 | 9 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-09-15 01:56 | yes | 0 | 12 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-09-15 04:06 | yes | 0 | 75 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-09-15 04:00 | yes | 0 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-09-15 04:20 | yes | 0 | 40 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-09-14 23:19 | yes | 0 | 49 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-09-14 23:13 | yes | 0 | 90 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-09-15 02:36 | yes | 0 | 28 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-09-15 03:43 | yes | 13 | 14 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-09-15 03:26 | yes | 6 | 8 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-09-15 00:38 | yes | 11 | 23 s |
| Comparative | Perplexity Sonar | sonar | 2026-09-15 04:16 | yes | 20 | 23 s |
| Comparative | Grok 4.20 | spacexai/grok-4.1-fast-non-reasoning via vertex (asked for grok-4.20-non-reasoning; the API answered as this version) | 2026-09-15 02:45 | yes | 0 | 9 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-09-15 02:01 | yes | 0 | 10 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-09-14 23:11 | yes | 0 | 71 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-09-15 00:18 | yes | 0 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-09-15 04:06 | yes | 0 | 28 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-09-14 23:47 | yes | 0 | 46 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-09-15 00:10 | yes | 0 | 86 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-09-15 01:08 | yes | 0 | 14 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-09-15 02:15 | yes | 34 | 16 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-09-14 23:31 | yes | 7 | 5 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-09-15 04:53 | yes | 9 | 30 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-09-15 00:10 | yes | 20 | 11 s |
| Budget constrained | Grok 4.20 | spacexai/grok-4.1-fast-non-reasoning via vertex (asked for grok-4.20-non-reasoning; the API answered as this version) | 2026-09-15 04:02 | yes | 0 | 12 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-09-15 02:32 | yes | 0 | 9 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via fireworks | 2026-09-15 00:17 | yes | 0 | 34 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-09-15 05:03 | yes | 0 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-09-15 01:24 | no | 0 | 40 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-09-15 00:36 | yes | 0 | 56 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-09-15 04:47 | yes | 0 | 44 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-09-15 00:47 | yes | 0 | 14 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-09-15 03:00 | yes | 23 | 18 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-09-15 04:01 | yes | 6 | 7 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-09-15 04:04 | yes | 11 | 26 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-09-15 02:23 | yes | 20 | 14 s |
| Scale constrained | Grok 4.20 | spacexai/grok-4.1-fast-non-reasoning via vertex (asked for grok-4.20-non-reasoning; the API answered as this version) | 2026-09-15 03:07 | yes | 0 | 10 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-09-14 23:09 | yes | 0 | 16 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via fireworks | 2026-09-15 04:11 | yes | 0 | 30 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-09-15 03:22 | yes | 0 | 2 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-09-14 23:18 | no | 0 | 37 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-09-15 03:32 | yes | 0 | 54 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-09-15 03:47 | yes | 0 | 30 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-09-15 01:07 | yes | 0 | 19 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-09-15 01:30 | yes | 27 | 17 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-09-14 23:12 | no | 0 | 7 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-09-14 23:17 | yes | 22 | 31 s |
| Negative framing | Perplexity Sonar | sonar | 2026-09-15 01:05 | yes | 20 | 7 s |
| Negative framing | Grok 4.20 | spacexai/grok-4.1-fast-non-reasoning via vertex (asked for grok-4.20-non-reasoning; the API answered as this version) | 2026-09-15 01:22 | yes | 0 | 13 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-09-15 03:38 | yes | 0 | 10 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via fireworks | 2026-09-15 02:24 | yes | 0 | 41 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-09-15 00:13 | yes | 0 | 2 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-09-15 04:09 | yes | 0 | 48 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-09-14 23:45 | yes | 0 | 69 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-09-14 23:27 | yes | 0 | 101 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-09-14 23:57 | yes | 0 | 49 s |
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
ShowHide
Category-scoped readings
Adobe read as Adobe Real-Time CDP
Adobe CDP read as Adobe Real-Time CDP
Azure Synapse read as Microsoft Azure Synapse Analytics
Databricks read as Databricks SQL Warehouse
Databricks (Lakehouse) read as Databricks SQL Warehouse
Oracle read as Oracle Autonomous Data Warehouse
RudderStack read as RudderStack Reverse ETL
Unresolved, counted raw
AWS Glue
Apache Druid
Bracket
Original Amazon Redshift
Responsys
SQL Server
Salesforce
Segement/RudderStack
Stitchdata
Tealium Data Cloud
Vertica
mParticle Warehouse Sync
Discontinued, still offered
No shut-down product was recommended here.