(airflow) branch main updated: Clarify Airflow's focus on batch-oriented workflows (#65723)

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in repository https://gitbox.apache.org/repos/asf/airflow.git


The following commit(s) were added to refs/heads/main by this push:
     new dade40feff4 Clarify Airflow's focus on batch-oriented workflows (#65723)
dade40feff4 is described below

commit dade40feff4c06169c66f75375fbf94ce5136492
Author: rstoof <gi...@ruudstoof.com>
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.