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Pros & Cons summary

Buyer's Guide

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Prominent pros & cons

PROS

Apache Airflow provides a stable and flexible platform for automating workflows, making it an ideal choice for low to middle-scale tasks.
Its integration capabilities with various technologies make it valuable for constructing complex data pipelines and supporting a wide range of operations.
The use of DAGs in Apache Airflow allows for excellent workload management and task orchestration, providing a clear visualization of relationships and configurations.
Apache Airflow's programmatic nature, utilizing Python for pipeline definitions, enables users to automate workflows efficiently and with great flexibility.
Apache Airflow's direct support for Python, a key language in data science and engineering, ensures ease of use and helps streamline automation efforts.

CONS

Apache Airflow lacks sufficient technical support, leading users to rely on external resources like Google for solutions.
There are issues with Apache Airflow's scalability, especially when handling extensive workflows of thousands of tasks.
Apache Airflow is not suitable for real-time ETL tasks or frequent job scheduling, such as every minute or five minutes.
Apache Airflow requires substantial manual intervention due to inadequate automation for daily activities and workflow monitoring.
Apache Airflow's maintenance complexity poses challenges, particularly when upgrading or managing its dependencies in a Kubernetes environment.
 

Apache Airflow Pros review quotes

reviewer2754210 - PeerSpot reviewer
Administrator at a tech vendor with 201-500 employees
Feb 20, 2026
The features and capabilities of Apache Airflow that I have found the most valuable and useful so far include its rich integration with many technologies.
Madhan Potluri - PeerSpot reviewer
Head Of Data at Ekar
Apr 23, 2025
Apache Airflow is a stable and flexible platform.
Kemal Duman - PeerSpot reviewer
Team Lead, Data Engineering at Nesine.com
Dec 25, 2024
Apache Airflow is easy to scale and its UI improves with each release.
Learn what your peers think about Apache Airflow. Get advice and tips from experienced pros sharing their opinions. Updated: September 2026.
913,683 professionals have used our research since 2012.
JR
Sr. Team Lead - IT at InfoStretch
Dec 24, 2024
Apache Airflow is easy for us to use to build machine learning models, transport data, and manage our infrastructure.
Sanket Suhagiya - PeerSpot reviewer
Senior Data Engineer at a consultancy with 10,001+ employees
Sep 30, 2024
The core features are strong, which are supported by Apache Airflow variables, DAGs, and connections.
FB
Product Owner at La Poste S.A.
Jan 15, 2024
We're running it on a virtual server, which we can easily upgrade if needed.
Damian Bukowski - PeerSpot reviewer
Program Python at Santander Bank Polska
Sep 28, 2023
Apache Airflow is in Python language, making it easy to use and learn.
Prathamesh D Marathe - PeerSpot reviewer
Senior Software Engineer at Annalect India
May 27, 2024
Apache Airflow can be integrated or used to run multiple files.
ManojKumar43 - PeerSpot reviewer
Big Data Engineer at BigTapp Analytics Pte Ltd
Mar 22, 2024
Apache Airflow is easy to use and can monitor task execution easily. For instance, when performing setup tasks, you can conveniently view the logs without delving into the job details.
Miodrag Milojevic - PeerSpot reviewer
Senior Data Archirect at Yettel
Feb 29, 2024
Its user-friendly interface makes it straightforward to operate, offering a plethora of features for data preparation, buffering, and format conversion.
 

Apache Airflow Cons review quotes

reviewer2754210 - PeerSpot reviewer
Administrator at a tech vendor with 201-500 employees
Feb 20, 2026
The stability and reliability of Apache Airflow cannot be praised as a great reliable application, but for small-scale solutions and small-scale use cases, we can always rely on Apache Airflow.
Madhan Potluri - PeerSpot reviewer
Head Of Data at Ekar
Apr 23, 2025
Currently, Apache Airflow is closely coupled, limiting the ability to link to outside channels by ourselves.
Kemal Duman - PeerSpot reviewer
Team Lead, Data Engineering at Nesine.com
Dec 25, 2024
It is not suitable for real-time ETL tasks.
Learn what your peers think about Apache Airflow. Get advice and tips from experienced pros sharing their opinions. Updated: September 2026.
913,683 professionals have used our research since 2012.
JR
Sr. Team Lead - IT at InfoStretch
Dec 24, 2024
There is a minor issue with the manual work in Airflow, as everyday activities are managed manually. There is no dashboard for us to check all the Directed Acyclic Graphs (DAGs); a dashboard would help us analyze the work better.
Sanket Suhagiya - PeerSpot reviewer
Senior Data Engineer at a consultancy with 10,001+ employees
Sep 30, 2024
The UI is a little bit outdated according to modern standards.
FB
Product Owner at La Poste S.A.
Jan 15, 2024
The automation capabilities could be improved; a visual workflow designer and a graphical tool to reduce coding would be very helpful. But for now, it's sufficient for our simple workflows.
Damian Bukowski - PeerSpot reviewer
Program Python at Santander Bank Polska
Sep 28, 2023
I want to see Apache Airflow have more integrations with more production-based databases since it is an area where the product lacks currently.
Prathamesh D Marathe - PeerSpot reviewer
Senior Software Engineer at Annalect India
May 27, 2024
The in-built package dependencies in Python have some issues in Apache Airflow, making it an area that needs improvement.
ManojKumar43 - PeerSpot reviewer
Big Data Engineer at BigTapp Analytics Pte Ltd
Mar 22, 2024
Airflow should support the dynamic drag creation.
Miodrag Milojevic - PeerSpot reviewer
Senior Data Archirect at Yettel
Feb 29, 2024
It would be beneficial to improve the pricing structure.