Workflow orchestration for enterprise buyers
Asked as “workflow orchestration tool”, and as “data pipeline orchestrator”, on behalf of an enterprise B2B company. 54 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
26%
Contested · Prefect 13%
26Apache Airflow13Prefect09Camunda52others
26% of first choices, contested.
Since September 2026▼−1Since September 2026: 29% → 27%, −1 point. Inside the 11-point floor: within noise. Read over the models both editions asked.Apache Airflow held the lead, −1 point on 29%, 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
Make24%Contested↗new leaderNew leader since September 2026: Make (23%) replaces Prefect (23% then, 21% now), 2 points clear, inside the 11-point floor.Standing →Mid-market
Prefect21%Contested=heldSince September 2026: 24% → 24%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.Standing →Enterprise
Apache Airflow26%Contested▼−1Since September 2026: 29% → 27%, −1 point. Inside the 11-point floor: within noise. Read over the models both editions asked.This page
Make24%Contested↗new leaderNew leader since September 2026: Make (23%) replaces Prefect (23% then, 21% now), 2 points clear, inside the 11-point floor.Standing →Mid-marketPrefect21%Contested=heldSince September 2026: 24% → 24%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.Standing →EnterpriseApache Airflow26%Contested▼−1Since September 2026: 29% → 27%, −1 point. Inside the 11-point floor: within noise. Read over the models both editions asked.This pageThe standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all fourteen models, for an enterprise B2B company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince September 2026
01Apache Airflow26%25%61accepted challenger▼−1Since September 2026: 29% → 27%, −1 point. Inside the 11-point floor: within noise. Read over the models both editions asked.29% → 27%
Apache Airflow26%25%61accepted challenger▼−1Since September 2026: 29% → 27%, −1 point. Inside the 11-point floor: within noise. Read over the models both editions asked.29% → 27%02Prefect13%9%44accepted challenger▲+8Since September 2026: 6% → 15%, +8 points. Inside the 11-point floor: within noise. Read over the models both editions asked.6% → 15%
Prefect13%9%44accepted challenger▲+8Since September 2026: 6% → 15%, +8 points. Inside the 11-point floor: within noise. Read over the models both editions asked.6% → 15%03
Temporal9%6%47accepted challenger=heldSince September 2026: 8% → 8%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.8% → 8%
Temporal9%6%47accepted challenger=heldSince September 2026: 8% → 8%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.8% → 8%04
Dagster9%13%45accepted challenger▲+6Since September 2026: 2% → 8%, +6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 8%
Dagster9%13%45accepted challenger▲+6Since September 2026: 2% → 8%, +6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 8%05
Camunda9%3%33accepted challenger▼−2Since September 2026: 8% → 6%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.8% → 6%
Camunda9%3%33accepted challenger▼−2Since September 2026: 8% → 6%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.8% → 6%06
Workato6%15%20accepted challenger▲+4Since September 2026: 2% → 6%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 6%
Workato6%15%20accepted challenger▲+4Since September 2026: 2% → 6%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 6%07BMC Control-M6%25%20criticized challenger▲+4Since September 2026: 2% → 6%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 6%
08
Astronomer Astro4%10%21accepted challenger▼−6Since September 2026: 10% → 4%, −6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.10% → 4%
Astronomer Astro4%10%21accepted challenger▼−6Since September 2026: 10% → 4%, −6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.10% → 4%09
AWS Step Functions2%29%21criticized challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 2%
AWS Step Functions2%29%21criticized challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 2%10
Microsoft Power Automate2%53%17criticized challenger▼−6Since September 2026: 6% → 0%, −6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.6% → 0%
Microsoft Power Automate2%53%17criticized challenger▼−6Since September 2026: 6% → 0%, −6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.6% → 0%Show the six products at 0%, ordered by negative rate
16
Zapier0%72%18criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
Zapier0%72%18criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%14
ServiceNow0%42%12criticized challenger▼−2Since September 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 0%
ServiceNow0%42%12criticized challenger▼−2Since September 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 0%15
n8n0%42%12criticized challenger▼−2Since September 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 0%
n8n0%42%12criticized challenger▼−2Since September 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 0%13
Kestra0%30%10criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
Kestra0%30%10criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%11
Argo Workflows0%12%16accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
Argo Workflows0%12%16accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%12
Google Cloud Composer Lab in the set0%0%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%
Google Cloud Composer Lab in the set0%0%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 Cloud Composer 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 zero times of 4; the other thirteen models zero times of 52. Lab treatment is defined on the method page; the row is marked, not excluded.
All twenty-eight head-to-head pages: the top eight products, each against each
Prefect vs MakePrefect vs WorkatoPrefect vs KestraPrefect vs ZapierApache Airflow vs DagsterApache Airflow vs n8nApache Airflow vs MakeApache Airflow vs WorkatoApache Airflow vs KestraApache Airflow vs ZapierDagster vs n8nDagster vs MakeDagster vs WorkatoDagster vs KestraDagster vs Zapiern8n vs Maken8n vs Workaton8n vs Kestran8n vs ZapierMake vs WorkatoMake vs KestraMake vs ZapierWorkato vs KestraWorkato vs ZapierKestra vs Zapier
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 →
010203040506B07
080910111213141516Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative40%
Key
01Apache Airflow26%
Apache Airflow26%02Prefect13%
Prefect13%03Temporal9%
Temporal9%04Dagster9%
Dagster9%05Camunda9%
Camunda9%06Workato6%
Workato6%07BMC Control-M6%
08Astronomer Astro4%
Astronomer Astro4%09AWS Step Functions2%
AWS Step Functions2%10Microsoft Power Automate2%
Microsoft Power Automate2%11Argo Workflows0%
Argo Workflows0%12Google Cloud Composer0%
Google Cloud Composer0%13Kestra0%
Kestra0%14ServiceNow0%
ServiceNow0%15n8n0%
n8n0%16Zapier0%
Zapier0%What they warned about
One 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, DeepSeek V4 Flash, Llama 4 Maverick, Qwen 3.7 Flash, 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.
Zapier72%
13 of 18 labels negative · 11 of 14 models · 8 hard negative
“**Consumer/business-user automation tools** such as **Zapier** or **Make** when the use case is mission-critical enterprise orchestration... can become a poor fit” Perplexity Sonar, negative prompt
Apache Airflow25%
15 of 61 labels negative · 11 of 14 models · 2 hard negative
“Tools to **Avoid or Be Highly Cautious With**: 1. **Apache Airflow**: - **Why?** ... maintenance nightmares with complex, monolithic workflows” Grok 4.1 Fast, negative prompt
Microsoft Power Automate53%
9 of 17 labels negative · 8 of 14 models
“geared towards Microsoft-stack organizations but may not be suitable for large enterprises due to its limitations in full-stack workload orchestration depth” Llama 4 Maverick, negative prompt
Make89%
8 of 9 labels negative · 7 of 14 models · 7 hard negative
“such as **Zapier** or **Make** when the use case is mission-critical enterprise orchestration, since they are positioned for business-user automations” Perplexity Sonar, 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
78 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. 1090 links across 288 sites, every framing counted. Ranked by the number of answers carrying the site or page. 7 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 · Kestra33 answers · 61 citations · 12 models
vendor site · Elementum27 answers · 30 citations · 11 models
vendor site · LarkSuite26 answers · 39 citations · 11 models
vendor site · Wrike23 answers · 28 citations · 11 models
vendor site · Teamwork.com23 answers · 24 citations · 10 models
vendor site · Cognism22 answers · 26 citations · 10 models
vendor site · Beta Systems22 answers · 23 citations · 11 models
vendor site · BMC21 answers · 32 citations · 10 models
21 answers · 24 citations · 8 models
vendor site · Zapier19 answers · 22 citations · 9 models
17 answers · 20 citations · 10 models
vendor site · ONES.com16 answers · 19 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.
23 answers · 10 models
23 answers · 10 models
23 answers · 11 models
21 answers · 10 models
20 answers · 10 models
19 answers · 10 models
16 answers · 10 models
15 answers · 6 models
14 answers · 10 models
13 answers · 7 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 workflow orchestration tool”, “workflow orchestration tool”, “workflow orchestration tools”. 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 |
|---|---|---|---|---|---|---|---|
| Apache Airflow apache.org | 26% | 220 | 8,100 | 271 | 1,144,025 | 0 | |
| Prefect prefect.io | 13% | 142 | 14,800 | 1,159 | 8,198 | $691 | 6 |
| Temporal temporal.io | 9% | 92 | 49,500 | 13,896 | 41,181 | 70 | |
| Dagster dagster.io | 9% | 147 | 5,400 | 143 | 23,407 | 34 | |
| Camunda camunda.com | 9% | 61 | 5,400 | 237 | 13,960 | 35 | |
| Workato workato.com | 6% | 64 | 14,800 | 405 | 38,042 | $20 | 120 |
| BMC bmc.com BMC Control-M 6% | 6% | 31 | 480 | 11 | 188,432 company | $29 | 63 |
| Astronomer astronomer.io Astronomer Astro 4% | 4% | 41 | 170 | 12 | 77,826 company | 46 | |
| Stonebranch Universal Automation Center stonebranch.com | 4% | 10 | |||||
| AWS parent site AWS Step Functions 2% | 2% | 39 | 368,000 | 114,001 |
Google's top ten for the three searches hold 17 sites; 2 of them are among the sites the models cited here (elementum.ai, teamwork.com). The first result for “best workflow orchestration tool” is guptadeepak.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 workflow orchestration tool for an enterprise B2B company?”Paraphrase“Which data pipeline orchestrator would you recommend to a large B2B company with thousands of employees?”Comparative“What are the top enterprise-grade workflow orchestration tools and how do they differ?”Budget-constrained“What is the best workflow orchestration tool 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 workflow orchestration tool. What should we look at?”Negative“Which workflow orchestration tools should a large enterprise avoid or be cautious about?”
Claude Haiku 4.5Apache Airflow, PrefectApache AirflowChangedno first choiceagainst: Microsoft Power AutomateEnateagainst: Pegano first choiceagainst: Apache Airflow, Microsoft Power Automate, Next Matter, Pega, ServiceNow, Zapier
Two alternatives
Dagster, Kubernetes WorkflowsFour alternatives
Astronomer Astro, Google Cloud Composer, Informatica, TalendTwo alternatives
Camunda, Microsoft Power AutomateGPT-5.4 miniTemporalagainst: DagsterApache AirflowChangedTemporalApache Airflowno first choiceagainst: AWS Step Functions, Apache Airflow
Two alternatives
Apache Airflow, PrefectOne alternative
DagsterThree alternatives
AWS Step Functions, Apache Airflow, CamundaTwo alternatives
Dagster, TemporalGemini 3.5 FlashWorkatoagainst: Apache AirflowAstronomer Astro, Dagster, PrefectChangedDagsteragainst: Apache Airflowno first choiceDagster, Prefectagainst: AWS Step Functions, Apache Airflow, Azure Data Factory, BizTalk, Cron, Luigi, Make, Microsoft Power Automate, Tibco, Zapier
Five alternatives
AWS Step Functions, Astronomer Astro, Camunda, Dagster, TemporalTwo alternatives
Databricks Lakeflow Jobs, Snowflake TasksFive alternatives
BMC Control-M, Kestra, Prefect, Stonebranch Universal Automation Center, TemporalFive alternatives
Apache Airflow, Astronomer Astro, Camunda, Temporal, UiPathPerplexity SonarWorkatoApache AirflowChangedno first choiceLarkagainst: BMC Control-M, Workatono first choiceagainst: Apache Airflow, Make, Zapier
Five alternatives
Apache Airflow, BMC Control-M, Camunda, Pega, ServiceNowOne alternative
DagsterSeven alternatives
Apache Airflow, BMC Control-M, Camunda, ServiceNow, Temporal, UiPath, WorkatoOne alternative
Microsoft Power AutomateGrok 4.1 FastApache Airflowagainst: TemporalApache AirflowHeldagainst: AWS Glue, Azure Data Factory, GCP DataflowApache Airflowagainst: AWS Step Functions, Azure Data Factory, BMC Control-M, IBM Workflow OrchestrationBMC Control-Magainst: Apache Airflow, Argo Workflows, Dagster, Prefect, TemporalPrefectagainst: Apache Airflow, Argo Workflows, Astronomer Astro, Camunda, Dagster, Make, Microsoft Power Automate, Prefect, ServiceNow, Workato, Zapier, n8n
Five alternatives
Appian, Astronomer Astro, Dagster, Prefect, ServiceNowFive alternatives
Amazon Managed Workflows for Apache Airflow, Astronomer Astro, Dagster, Google Cloud Composer, PrefectSix alternatives
Argo Workflows, Dagster, Flyte, Kestra, Netflix Conductor, PrefectFive alternatives
Airflow managed, Temporal, Workato, Zapier, n8nMistral SmallCleo, Netflix Conductoragainst: IBM Workflow OrchestrationDagster, PrefectChangedno first choiceAWS Step Functions, Azure Logic Appsno first choicenothing named
One alternative
OpConFour alternatives
Apache Airflow, Argo Workflows, Azure Data Factory, Databricks Lakeflow JobsTwo alternatives
Camunda Platform 8, ServiceNow Automation EngineDeepSeek V4 FlashCamundaApache AirflowChangedagainst: Informatica, Kestra, Matillion, Prefect, SnapLogicApache AirflowBMC Control-M, Stonebranch Universal Automation Centeragainst: ActiveBatch, Astronomer Astro, Dagster, Make, Zapierno first choiceagainst: Apache Airflow, BMC Control-M, IFTTT, Kestra, Make, Tidal, Zapier
Two alternatives
Apache Airflow, TemporalThree alternatives
Amazon Managed Workflows for Apache Airflow, Astronomer Astro, DagsterSix alternatives
AWS Step Functions, Argo Workflows, Camunda, Dagster, Prefect, TemporalThree alternatives
Apache Airflow, Prefect, TemporalTwo alternatives
Prefect, TemporalLlama 4 Maverickno first choiceBMC Control-M, Stonebranch Universal Automation CenterChangedno first choiceno first choiceno first choiceagainst: Apache Airflow, Microsoft Power Automate, ServiceNow
Qwen 3.7 FlashApache Airflow, Astronomer AstroDagsterChangedApache Airflowagainst: AWS Step FunctionsApache Airflowagainst: AWS Step Functions, Zapierno first choiceagainst: Apache Oozie, Borland StarTeam, Google AppSheet, IBM Sterling B2B, IFTTT, Kissflow, Make, Microsoft Power Automate, Oracle Siebel, Zapier
Five alternatives
Dagster, IBM Cloud Pak for Automation, Prefect, Temporal, WorkatoTwo alternatives
Apache Airflow, Astronomer AstroThree alternatives
BMC Control-M, Prefect, TemporalThree alternatives
Frends, Microsoft Power Automate, TemporalKimi K2Camundaagainst: ZapierApache AirflowChangedApache AirflowApache Airflow, Temporalagainst: Camunda SaaS, Prefect, TemporalCamunda, Prefectagainst: Apache Airflowagainst: Apache Airflow, BMC Control-M, Broadcom Automic Automation, Dagster, IBM Business Automation Workflow, Kestra, Oracle BPM, Redwood RunMyJobs, n8n
Three alternatives
Apache Airflow, Temporal, WorkatoThree alternatives
Astronomer Astro, Dagster, PrefectSix alternatives
Argo Workflows, Camunda, Dagster, Kestra, Prefect, TemporalFour alternatives
Argo Workflows, BMC Control-M, Camunda Self-Managed, TidalTwo alternatives
Temporal, ZapierGLM 4.7 FlashXTemporalApache AirflowChangedApache AirflowTemporalno first choiceagainst: Apache Airflow, Appian, Dagster, Inngest, Make, Microsoft Power Automate, Netflix Conductor, Orkes Conductor, Pega, Pipedream, Salesforce Flow, ServiceNow, Trigger.dev, UiPath, Zapier, n8n
Three alternatives
BMC Control-M, Camunda, WorkatoOne alternative
DagsterSix alternatives
Apache NiFi, Argo Workflows, Camunda, Dagster, Prefect, TemporalTwo alternatives
Astronomer Astro, CamundaMiniMax M2.5WorkatoDatabricks Lakeflow Jobs, PrefectChangedno first choiceno first choiceno first choiceagainst: Make, Workato, Zapier, n8n
Four alternatives
Apache Airflow, Boomi, Camunda, ServiceNow Workflow OrchestratorTwo alternatives
Apache Airflow, DagsterFive alternatives
Nexquira, ORO Labs, Prefect, Workato, ZapierGPT-6 LunaTemporalDagsterChangedApache AirflowMicrosoft Power Automateno first choiceagainst: Apache Airflow, Microsoft Power Automate, Self-hosted n8n, Zapier
Four alternatives
Apache Airflow, Camunda, Dagster, WorkatoOne alternative
Apache AirflowNine alternatives
AWS Step Functions, Argo Workflows, Azure Logic Apps, BMC Control-M, Camunda, Dagster, Google Cloud Workflows, Prefect, TemporalTwo alternatives
Camunda, TemporalMuse Glimmer 30BCamundaApache AirflowChangedApache AirflowCamundaagainst: AWS Step Functions, Google Cloud Workflowsno first choiceagainst: Apache Airflow, BMC Control-M, Broadcom Automic/AutoSys, Kissflow, Microsoft Power Automate, Nintex, ServiceNow, Teamwork.com, Zapier, n8n
Three alternatives
Apache Airflow, Cleo Integration Cloud, TemporalFour alternatives
Astronomer Astro, Azure Data Factory, Dagster, PrefectThirteen alternatives
ActiveBatch, Argo Workflows, BMC Control-M, Camunda, Dagster, IBM Workflow Orchestration, Microsoft Power Automate, Prefect, Redwood RunMyJobs, Stonebranch Universal Automation Center, Temporal, UiPath, WorkatoThree alternatives
Apache Airflow, Microsoft Power Automate, TemporalBold 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 09:21 | no | 0 | 5 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 11:18 | yes | 4 | 5 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 13:15 | yes | 18 | 29 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-01 11:16 | yes | 20 | 5 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:18 | yes | 25 | 9 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 09:06 | yes | 9 | 5 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 12:30 | yes | 22 | 24 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 08:49 | yes | 5 | 2 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 08:09 | yes | 14 | 81 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:48 | yes | 14 | 21 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 12:40 | yes | 24 | 26 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 11:19 | yes | 5 | 10 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-01 12:32 | yes | 4 | 11 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:50 | yes | 15 | 20 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 12:01 | yes | 9 | 7 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 12:33 | yes | 2 | 4 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 10:09 | yes | 7 | 23 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-01 13:26 | yes | 16 | 3 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 12:02 | yes | 23 | 8 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 08:18 | yes | 13 | 9 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 13:33 | yes | 20 | 33 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 08:49 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 12:58 | no | 0 | 30 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 12:56 | yes | 15 | 15 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 13:29 | yes | 25 | 61 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 10:53 | yes | 5 | 23 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-01 07:50 | yes | 2 | 17 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 10:42 | yes | 15 | 22 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:23 | yes | 15 | 12 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:35 | yes | 8 | 7 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:58 | yes | 18 | 29 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-01 12:50 | yes | 20 | 7 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 12:56 | yes | 21 | 10 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 12:17 | yes | 10 | 10 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 09:48 | yes | 23 | 50 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 12:27 | yes | 5 | 3 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 13:31 | yes | 15 | 65 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 09:12 | yes | 15 | 27 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:11 | no | 0 | 36 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 12:11 | yes | 5 | 15 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-01 08:00 | yes | 10 | 42 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 07:54 | yes | 15 | 29 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 12:05 | yes | 15 | 8 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:47 | yes | 3 | 4 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 12:42 | no | 0 | 6 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-01 12:52 | yes | 17 | 4 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 09:00 | yes | 24 | 8 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:03 | yes | 5 | 5 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 12:28 | yes | 23 | 41 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 08:16 | yes | 5 | 1 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 11:53 | yes | 10 | 36 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 11:20 | yes | 24 | 49 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:30 | yes | 23 | 59 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 13:31 | yes | 20 | 54 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 13:53 | yes | 3 | 17 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 10:51 | yes | 20 | 39 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 13:39 | yes | 16 | 13 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:27 | yes | 0 | 6 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 10:09 | yes | 12 | 30 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-01 13:04 | yes | 20 | 5 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 09:21 | yes | 14 | 8 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 09:49 | no | 0 | 11 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:57 | yes | 25 | 44 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 11:46 | yes | 5 | 3 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:55 | yes | 5 | 17 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:40 | yes | 24 | 32 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:12 | yes | 20 | 64 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 11:44 | yes | 15 | 21 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 13:02 | yes | 4 | 24 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:34 | yes | 14 | 24 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 10:09 | yes | 14 | 10 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 11:45 | yes | 5 | 6 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:42 | yes | 9 | 25 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-01 13:01 | yes | 18 | 4 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:35 | yes | 22 | 9 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 13:17 | yes | 17 | 10 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 11:04 | yes | 24 | 51 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 11:40 | yes | 5 | 2 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 07:59 | yes | 10 | 38 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 12:44 | yes | 25 | 27 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:15 | yes | 18 | 57 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 13:33 | yes | 24 | 48 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-01 08:50 | yes | 4 | 18 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:59 | yes | 13 | 27 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
Astronomer read as Astronomer Astro
Astronomer (Apache Airflow) read as Astronomer Astro
Astronomer (Astro) read as Astronomer Astro
Astronomer (Managed Apache Airflow) read as Astronomer Astro
Astronomer (managed Airflow) read as Astronomer Astro
Databricks read as Databricks Lakeflow Jobs
MuleSoft read as MuleSoft Anypoint Platform
MuleSoft (Salesforce) read as MuleSoft Anypoint Platform
Stonebranch read as Stonebranch Universal Automation Center
Stonebranch UAC (Universal Automation Center) read as Stonebranch Universal Automation Center
Unresolved, counted raw
Airflow managed (e.g., Astronomer)
Argo Events
BizTalk
Borland StarTeam
Camunda Platform 8
Camunda SaaS
Camunda Self-Managed (Enterprise Edition)
Creatio
Frends
Google AppSheet
Google Composer
HCL Workload Automation (HWA)
IBM AutoSys
IBM BAW
IBM Cloud Pak for Automation
IBM Sterling B2B
Knative
Kubernetes Workflows (Argo Workflows)
Nexquira
ORO Labs
OpCon
Oracle Siebel
Orkes Conductor
Qntrl
Red Hat Integration (Apicurio)
Redwood
Resolve
Salesforce Flow
Self-hosted n8n
ServiceNow Automation Engine
ServiceNow Workflow Orchestrator
Discontinued, still offered
No shut-down product was recommended here.