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new dade40feff4 Clarify Airflow's focus on batch-oriented workflows
(#65723)
dade40feff4 is described below
commit dade40feff4c06169c66f75375fbf94ce5136492
Author: rstoof <[email protected]>
AuthorDate: Thu Apr 23 18:53:05 2026 +0200
Clarify Airflow's focus on batch-oriented workflows (#65723)
Removed explanation about Airflow's suitability for streaming workloads and
its relationship with Apache Kafka.
---
airflow-core/docs/index.rst | 4 ----
1 file changed, 4 deletions(-)
diff --git a/airflow-core/docs/index.rst b/airflow-core/docs/index.rst
index fc2d641d306..4280171e42d 100644
--- a/airflow-core/docs/index.rst
+++ b/airflow-core/docs/index.rst
@@ -133,10 +133,6 @@ others via the `community
<https://airflow.apache.org/community>`_, `Slack <http
Why not Airflow®?
=================
-Airflow® is designed for finite, batch-oriented workflows. While you can
trigger Dags using the CLI or REST API, Airflow is not
-intended for continuously running, event-driven, or streaming workloads. That
said, Airflow often complements streaming systems like Apache Kafka.
-Kafka handles real-time ingestion, writing data to storage. Airflow can then
periodically pick up that data and process it in batch.
-
If you prefer clicking over coding, Airflow might not be the best fit. The web
UI simplifies workflow management, and the developer
experience is continuously improving, but defining workflows as code is
central to how Airflow works — so some coding is always required.
