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Apache Airflow pros and cons

Vendor: Apache

4.0 out of 5

36 reviews
97% willing to recommend

713 followers

Pros & Cons summary

Apache Airflow supports workflow automation by effectively automating data pipelines and warehouse processes with excellent integration capabilities, especially with Cloudera. Python support is critical for data science, ensuring programmatic ease. Despite its customization and flexibility, Airflow lacks efficient scalability in cloud environments, affecting larger workloads. Maintaining it can be challenging due to limited technical support. Enhancements in production-based database integration and cloud support are needed.

Buyer's Guide

Get pricing advice, tips, use cases and valuable features from real users of this product.

Prominent pros & cons

PROS

Apache Airflow supports automation and workflow management using Python, facilitating easy programmatic work and automation.

Its DAG presentation helps visualize relationships, making it configuration-driven and manageable.

Integration with other pipelines and solutions is smooth and effective, supporting complex operations.

Fast development and ease of use, especially with Python, contribute to efficient workflow automation and scheduling.

Customizability and flexibility allow users to easily define and manage pipelines in code, accommodating various frameworks.

CONS

Apache Airflow lacks certain out-of-the-box features and can require additional development for workflow description.

Scalability expectations of Apache Airflow are not met, particularly in cloud environments.

Maintenance of Apache Airflow can be complex, often needing manual intervention for restarting processes.

Apache Airflow requires coding in Python for building DAGs, lacking no-code or drag-and-drop capabilities.

Apache Airflow struggles with handling large workflows, often requiring workflows to be split due to performance issues.

Apache Airflow Pros review quotes

reviewer2108010

Associate Data Engineer at a outsourcing company with 201-500 employees

Feb 20, 2023

Development on Apache Airflow is really fast, and it's easy to use with the newer updates. Everything is in Python, so it's not hard to understand. They also have a graphical view, so if you are not a programmer and you are just an administrator, you can easily track everything and see if everything is working or not.

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SG

Engineering Manager - OTT Platform at Amagi

Apr 13, 2020

The reason we went with Airflow is its DAG presentation, that shows the relationships among everything. It's more of a configuration-driven workflow.

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reviewer1447245

Senior Solutions Architect/ Software Architect at a comms service provider with 51-200 employees

Dec 22, 2020

The product integrates well with other pipelines and solutions.

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SUDHIR KUMAR RATHLAVATH

Student at University of South Florida

Jul 26, 2023

Every feature in Apache Airflow is valuable. The number of operators and features I've used are mainly related to connectivity services and integrated services because I primarily work with GCP.

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Damian Bukowski

Program Python at Santander Bank Polska

Sep 28, 2023

Apache Airflow is in Python language, making it easy to use and learn.

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MW

Mohd Zaid Waqiyuddin Mohd Zulkifli

Analytics Solution Manager at Telekom Malaysia

Feb 11, 2021

The best part of Airflow is its direct support for Python, especially because Python is so important for data science, engineering, and design. This makes the programmatic aspect of our work easy for us, and it means we can automate a lot.

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Miodrag Milojevic

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.

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AN

Alexey Nadenenko

Solution Architect at EPAM Systems

Sep 4, 2019

This is a simple tool to automate using Python.

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Big Data Engineer at BigTapp Analytics

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.

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Nomena NY HOAVY

Lead Data Scientist at MVola

Jun 20, 2022

The solution is flexible for all programming languages for all frameworks.

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Apache Airflow Cons review quotes

reviewer2108010

Associate Data Engineer at a outsourcing company with 201-500 employees

Feb 20, 2023

Programmatically, it's very good, and it doesn't have any competitors, but you cannot develop anything in Airflow UI. You need to develop everything within the program. In the market, other tools have come up recently as competitors to Airflow, and they also give graphical programming options, whereas Airflow doesn't provide that feature currently. All the DAGs you want to build need to be coded in Python.

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SG

Engineering Manager - OTT Platform at Amagi

Apr 13, 2020

One specific feature that is missing from Airflow is that the steps of your workflow are not pipelined, meaning the stageless steps of any workflow. Not every workflow can be implemented within Airflow.

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reviewer1447245

Senior Solutions Architect/ Software Architect at a comms service provider with 51-200 employees

Dec 22, 2020

The scalability of the solution itself is not as we expected. Being on the cloud, it should be easy to scale, however, it's not.

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Free Report: Apache Airflow Reviews and More

Learn what your peers think about Apache Airflow. Get advice and tips from experienced pros sharing their opinions. Updated: December 2024.

823,875 professionals have used our research since 2012.

SUDHIR KUMAR RATHLAVATH

Student at University of South Florida

Jul 26, 2023

For admins, there should be improved logging capabilities because Apache Airflow does have logging, but it's limited to some database data.

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Damian Bukowski

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.

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MW

Mohd Zaid Waqiyuddin Mohd Zulkifli

Analytics Solution Manager at Telekom Malaysia

Feb 11, 2021

We're currently using version 1.10, but I understand that there's a lot of improvements in version 2. In the earlier version that we're using, we sometimes have problems with maintenance complexity. Actually using Airflow is okay, but maintaining it has been difficult.

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Miodrag Milojevic

Senior Data Archirect at Yettel

Feb 29, 2024

It would be beneficial to improve the pricing structure.

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AN

Alexey Nadenenko

Solution Architect at EPAM Systems

Sep 4, 2019

We need to develop our workflow description and notations because out of the box, Apache Airflow does not provide some features that are needed.

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Big Data Engineer at BigTapp Analytics

Mar 22, 2024

Airflow should support the dynamic drag creation.

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Nomena NY HOAVY

Lead Data Scientist at MVola

Jun 20, 2022

Apache Airflow could be improved by integrating some versioning principles.

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Product Categories

Product Categories

Business Process Management (BPM)

Popular Comparisons

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Informatica Intelligent Data Management Cloud (IDMC) vs Apache Airflow

Camunda vs Apache Airflow

Appian vs Apache Airflow

Pega Platform vs Apache Airflow

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