Apache Airflow Reviews & Product Details

Apache Airflow is an open-source platform designed for authoring, scheduling, and monitoring complex workflows. Developed in Python, it enables users to define workflows as code, facilitating dynamic pipeline generation and seamless integration with various technologies. Airflow's modular architecture and message queue system allow it to scale efficiently, managing workflows from single machines to large-scale distributed systems. Its user-friendly web interface provides comprehensive monitoring and management capabilities, offering clear insights into task statuses and execution logs. Key Features: - Pure Python: Workflows are defined using standard Python code, allowing for dynamic pipeline generation and easy integration with existing Python libraries. - User-Friendly Web Interface: A robust web application enables users to monitor, schedule, and manage workflows without the need for command-line interfaces. - Extensibility: Users can define custom operators and extend libraries to fit their specific environment, enhancing the platform's flexibility. - Scalability: Airflow's modular architecture and use of message queues allow it to orchestrate an arbitrary number of workers, making it ready to scale as needed. - Robust Integrations: The platform offers numerous plug-and-play operators for executing tasks across various cloud platforms and third-party services, facilitating easy integration with existing infrastructure. Primary Value and Problem Solving: Apache Airflow addresses the challenges of managing complex data workflows by providing a scalable and dynamic platform for workflow orchestration. By defining workflows as code, it ensures reproducibility, version control, and collaboration among teams. The platform's extensibility and robust integrations allow organizations to adapt it to their specific needs, reducing operational overhead and improving efficiency in data processing tasks. Its user-friendly interface and monitoring capabilities enhance transparency and control over workflows, leading to improved data quality and reliability.

Seller

The Apache Software Foundation

Discussions

Apache Airflow Community

Overview by

VIKASH KUMAR GUPTA (AZURE DATA ENGINEER at Capgemini Technology Services India Limited)

Value at a Glance

Averages based on real user reviews.

Time to Implement

3 months

Return on Investment

6 months

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Apache Airflow Integrations

(24)

Integration information sourced from real user reviews.

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Verified User in Banking

Small-Business (50 or fewer emp.)

9/8/2022

"It’s very nice DAG based job sheduling tool. I will recommend everyone to use at least once."

4.5/5

What do you like best about Apache Airflow?

It's very light weight and easy to use tool Review collected by and hosted on G2.com.

What do you dislike about Apache Airflow?

Nothing to dislike at the moment we have not dislike anything yet Review collected by and hosted on G2.com.

Verified User in Information Technology and Services

Small-Business (50 or fewer emp.)

9/6/2022

"Apache airrlfow is Awesome"

5/5

What do you like best about Apache Airflow?

The best thing about the Airflow is how simple it is to use and best UI experience Review collected by and hosted on G2.com.

What do you dislike about Apache Airflow?

As of now I have not felt any bad experiences about the apache airflow Review collected by and hosted on G2.com.

Verified User in Financial Services

Enterprise (> 1000 emp.)

9/8/2022

"Great experience working with airflow. Easy to use and great GUI."

5/5

What do you like best about Apache Airflow?

Creation of DAGS are really easy and graphical view of dag gives simple yet pretty picture of the complete flow. Review collected by and hosted on G2.com.

What do you dislike about Apache Airflow?

There should be retry option if a job fails. Review collected by and hosted on G2.com.

Verified User in Accounting

Mid-Market (51-1000 emp.)

9/14/2022

"Best Workflow management tool."

4/5

What do you like best about Apache Airflow?

1. UI 2. Open source 3. Monitoring workflow Review collected by and hosted on G2.com.

What do you dislike about Apache Airflow?

None as of now . Only the statsD metrics don't provide task level info. Review collected by and hosted on G2.com.

Verified User in Computer Software

Mid-Market (51-1000 emp.)

9/20/2022

"Airflow: Orchestration in cloud like Air"

4.5/5

What do you like best about Apache Airflow?

* Open source

* Integration capabilities

* Run anywhere

* No Cloud Monopoly Review collected by and hosted on G2.com.

What do you dislike about Apache Airflow?

* Containerisation problem

* More cloud integration Review collected by and hosted on G2.com.

Verified User in Computer & Network Security

Mid-Market (51-1000 emp.)

9/13/2022

"I have some experience in working with apache. It's easy to understand and write scripts."

4/5

What do you like best about Apache Airflow?

Apache proxy was most useful for me as I could connect different servers easily. Review collected by and hosted on G2.com.

What do you dislike about Apache Airflow?

Nothing as such I have found out at this moment. Review collected by and hosted on G2.com.

Giridhar P.

Data Engineer

Mid-Market (51-1000 emp.)

8/6/2021

"Apache airflow is an amazing data extraction, processing and scheduling tool!!!"

4.5/5

What do you like best about Apache Airflow?

Apache airflow is a freeware that executes components written in python modules. The written python modules are called DAGs. The DAGs need to configured with appropriate connections for successful execution. The connections and variables are easily configurable. The User Interface aspect of the tool makes the visualization the most attractive aspect of the tool. The triggering of the respective DAGs, status of execution, success and failure notification in green and red colors etc are some of the best aspects of Apache airflow. The configuration of variables in the form of json files are easy and straightforward. The different instances of executions along with the individual DAGs statuses historically enable the users to track the logs successfully. The ability to backtrack the logs for all these instances makes this tool a commendable one. Functions-based categorization of the functionality is flexible. Review collected by and hosted on G2.com.

What do you dislike about Apache Airflow?

Apache airflow contains an intensive documentation that needs to be read and reviewed to ensure that the configuration works per your needs. Knowledge of python as a prerequisite is needed. Familiarity with Json file and format is required to some extent. The tool might create an impression of being a bit complex to many users who don't have any background on Python. The formatting of tasks, hooks etc could be a bit complex. Not much of examples are available on open forums and exploring the solution for an end to end functionality could be a bit challenging for new users. Review collected by and hosted on G2.com.

Recommendations to others considering Apache Airflow:

If you want an ETL tool that requires some programming, this tool could be your first choice. The coding in Airflow is not GUI based and hence may not be conducive to all the ETL engineers. However, it could serve all your basic needs. The ability to connect to heterogeneous databases and perform a comparison across these datasets is a provision that is yet to arrive. Review collected by and hosted on G2.com.

What problems is Apache Airflow solving and how is that benefiting you?

Apache airflow is being used in my organization to perform data integration in AWS S3 region. The tool has enabled me to connect successfully to a relational database, perform data extracts and compile the accumulation of extracts in multiple flat file segments. The DAG components are conducive to build and the dependency of tasks within DAGs are easy to be specified. The end to end ETL functionality was implemented successfully using Apache airflow. The tool provides flexibility to trigger different DAGs at any time during the day and ensures that the logs are traced successfully. The tool can be configured successfully on either AWS environment or docker container. It was configured in both environments successfully within my organization and this flexibility is what makes it the best. Review collected by and hosted on G2.com.

Verified User in Consumer Services

Mid-Market (51-1000 emp.)

9/22/2022

"Good orchestrator tool to deal with dependency.."

4/5

What do you like best about Apache Airflow?

Different types of Operators and Trigger rules. Review collected by and hosted on G2.com.

What do you dislike about Apache Airflow?

Nothing as such but Web UI can be improved Review collected by and hosted on G2.com.

Verified User in Hospital & Health Care

Small-Business (50 or fewer emp.)

10/15/2021

"Data pipelines never been easier"

5/5

What do you like best about Apache Airflow?

Once you know the strengths of Ariflow create data pipelines is easier than ever before, the data lineage now is super clear since Airflow has a lot of visual integrations Review collected by and hosted on G2.com.

What do you dislike about Apache Airflow?

UI has lots of bug still, some times the UI will show bad or elements will appear in weird places and it would become impossible to click what you need, It happens often enough that it bothers Review collected by and hosted on G2.com.

Recommendations to others considering Apache Airflow:

Take a good Airflow introduction course, it's easy enough to learn it without it, but there are a ton of good practices that you should know to get the full benefits of Apache Airflow Review collected by and hosted on G2.com.

What problems is Apache Airflow solving and how is that benefiting you?

New data pipelines, previously data pipelines, and time triggers were done with an inhouse tool that gave us a lot of problems, Airflow brings a lot of standardization to the project as well as modularity to the code Review collected by and hosted on G2.com.