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Workflow orchestration · November 2026 Edition

Dagster vs Apache Airflow

One of fourteen models named Dagster first on the direct prompt; zero named Apache Airflow. Both were named by all fourteen models and Dagster carries 50 labels and Apache Airflow 69, so the shares are not directly comparable.

Dagster

accepted challenger

Named in three categories this edition.

Apache Airflow

criticized challenger

Named in two categories this edition.

First-choice share15%13%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate4%32%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#3A position in a field of 16; printed, not drawn.
Labels5069A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Dagster reading right to left. Rank and label count are printed, not drawn.n8n was named alongside these two in nine of the fourteen direct answers. Prefect vs Dagster · Prefect vs Apache Airflow · Dagster vs n8n

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; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the workflow orchestration page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
DagsterFirst choices, of fourteen modelsApache Airflow
Direct101 against Apache Airflow
Paraphrase735 against Apache Airflow
Comparative010
Budget-constrained033 against Apache Airflow
Scale-constrained011 against Apache Airflow
Negative322 against Dagster · 12 against Apache Airflow
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Across every category in the November 2026 Edition, Dagster and Apache Airflow were named in the same answer 144 times, of the 153 answers naming Dagster and the 244 naming Apache Airflow. In those answers Apache Airflow took the first choice forty-three times and Dagster fifteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Dagster and Apache Airflow stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.20
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
GPT-6 Luna
Muse Glimmer 30B
Dagster Apache Airflow first choice named as an alternative argued againstblank: not namedEach cell is one answer, Dagster on the left and Apache Airflow on the right.

The direct prompt

The plain question, one answer per model, grouped by where Dagster and Apache Airflow stood in it.

Dagster first, Apache Airflow not the choice

1 of 14 modelsApache Airflow was named in the answer but not as the choice, or not at all.
Gemini 3.5 FlashDagster, Prefect, Temporal, n8n alternatives: Amazon Managed Workflows for Apache Airflow, Astronomer Astro, Make

Neither was the first choice, one was named

5 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Prefect, Zapier/Make alternatives: Apache Airflow
GPT-5.4 miniTemporal alternatives: Apache Airflow, Prefect
Mistral SmallPrefect alternatives: Apache Airflow, Camunda Platform 8, Dagster, Microsoft Power Automate, Workato
Llama 4 MaverickPrefect alternatives: Apache Airflow, Dagster, Make, Microsoft Power Automate, Workato, Zapier, n8n
Qwen 3.7 FlashMake alternatives: Apache Airflow, Microsoft Power Automate, n8n

Neither was named

8 of 14 modelsThe answer made no first choice from these two in this category.
Perplexity SonarWorkato alternatives: Make, Microsoft Power Automate, Zapier, n8n
Grok 4.20Zapier alternatives: Camunda Platform 8, Make, Microsoft Power Automate, SnapLogic, Workato, n8n
DeepSeek V4 FlashWorkato alternatives: Make, Prefect, Zapier, n8n
Kimi K2Microsoft Power Automate, Zapier alternatives: Make, Workato, n8n
GLM 4.7 FlashXMake alternatives: Microsoft Power Automate, Tray.io, Workato, Zapier, n8n
MiniMax M2.5no first choice
GPT-6 LunaWorkato alternatives: Camunda Platform 8, Microsoft Power Automate, Temporal, n8n
Muse Glimmer 30BWorkato alternatives: Boomi, Make, Microsoft Power Automate, SnapLogic, Zapier

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Apache Airflow leads by two points.
Apache Airflow4%#5 of 10
Dagster2%#6 of 10
The full small business standing →
Mid-marketThe figures above
The order flips: Dagster leads at mid-market.
Dagster15%#2 of 16
Apache Airflow13%#3 of 16
The full mid-market standing →
Enterprise
The order flips: Apache Airflow leads at enterprise.
Apache Airflow29%#1 of 20
Dagster5%#5 of 20
The full enterprise standing →

What the models said about Dagster

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.

“Many current open core tools like Kestra and Dagster keep essential enterprise features ... locked behind their enterprise versions.” Muse Glimmer 30B · negative prompt · soft negative
“Dagster has a younger ecosystem with fewer integrations than Airflow” Claude Haiku 4.5 · negative prompt · soft negative
“Winner: Dagster (or Prefect) ... Dagster Cloud or Prefect Cloud are the top recommendations over traditional Apache Airflow.” Gemini 3.5 Flash · direct prompt · first choice
“Start with Dagster (specifically Dagster Plus/Apache Dagster) if you are building a greenfield stack today.” Qwen 3.7 Flash · paraphrase prompt · first choice
“Prefect or Dagster strike a good balance between ease of use, scalability, and observability” Mistral Small · paraphrase prompt · first choice

What the models said about Apache Airflow

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.

“running Airflow in production requires managing the scheduler, workers, metadata database, and web server, and it's not suited for business process automation or teams without Python expertise” Claude Haiku 4.5 · budget prompt · soft negative
“Unlike open-source Airflow, which often requires a dedicated data platform engineer to maintain Kubernetes clusters” Gemini 3.5 Flash · direct prompt · soft negative
“Apache Airflow is widely used but is frequently cited as a caution for teams without dedicated platform engineering” Muse Glimmer 30B · negative prompt · soft negative
“Airflow is the pioneer of modern code-as-configuration workflows... Choose Apache Airflow if you operate in a traditional enterprise data setting” Gemini 3.5 Flash · comparative prompt · first choice
“The industry standard and most widely adopted open-source orchestrator... Choose Airflow if you need the largest ecosystem” DeepSeek V4 Flash · comparative prompt · first choice
“The industry-standard, open-source data pipeline scheduler ... Largest ecosystem of operators and integrations” GLM 4.7 FlashX · comparative prompt · first choice
Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.