--- title: Apache Airflow Reviews meta\_title: 'Apache Airflow Reviews 2026: Details, Pricing, & Features | G2' meta\_description: Filter 130 reviews by the users' company size, role or industry to find out how Apache Airflow works for a business like yours. aggregate\_rating: rating\_value: 4.4 review\_count: 130 scale: '5' date\_modified: '2026-08-07' parent\_category: name: Artificial Intelligence url: https://www.g2.com/categories/artificial-intelligence ---

# Apache Airflow Reviews & Product Details

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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.

* * *

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Discussions
[Apache Airflow Community](https://www.g2.com/products/apache-airflow/discuss)
Solution Type

Best-of-Breed

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

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## Value at a Glance

Averages based on real user reviews.

### Time to Implement

3 months

### Return on Investment

6 months

[
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## User Insights

Average based on 130 real user reviews.

Implementation Time

3 months

Perceived Cost

$$$$$

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## Apache Airflow Integrations
(17)

What do users say about integrations?

Integration information sourced from real user reviews.

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 ![Salman K.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Salman K.")
SK

Salman K.

Subordinate Consultant

Information Technology and Services

Enterprise (\> 1000 emp.)

3/17/2026

"Apache Airflow : Flexible and reliable orchestration tool with a learning curve"

4/5

What do you like best about Apache Airflow?

What I like most about Airflow is its flexibility and number of features for building workflows using DAGs. It is very useful for managing complex pipelines with dependencies. Integration with different systems is also strong. Once setup is done, it works reliably and is used frequently in day-to-day operations. Review collected by and hosted on G2.com.

What do you dislike about Apache Airflow?

Ease of use is one area where it can improve, especially for new users. Initial setup and implementation take effort if you are managing it yourself. The UI is not very user-friendly and sometimes slow. Also, debugging failed workflows can take time. Review collected by and hosted on G2.com.

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

Airflow is helping us automate and manage data pipelines in a structured way. Earlier, tasks were manual and not properly scheduled, but now everything runs through defined workflows. It has improved reliability, reduced manual effort, and made it easier to monitor processes. Integration with multiple systems also helps in handling end-to-end data flow efficiently. Review collected by and hosted on G2.com.

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Current UserValidated ReviewerIncentivizedSource: G2 invite

 ![Shabbir P.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Shabbir P.")
SP

Shabbir P.

Senior Software Engineer

Small-Business (50 or fewer emp.)

12/11/2025

"Powerful Task Scheduler with Installation Challenges"

4/5

What do you like best about Apache Airflow?

I use Apache Airflow for project flow management and monitoring. I find its web-based UI and Python scripting features valuable, making it easy to develop and design process flows. Python as a scripting language is more user-friendly than other complex languages, which helps in writing complex flowcharts better than with traditional languages. Review collected by and hosted on G2.com.

What do you dislike about Apache Airflow?

The installation process of Apache Airflow is quite complex and highly dependent on PIP, making it very difficult to handle on cyber security blocked servers. The initial setup is challenging, especially in a proxy-based environment, as it requires lots of permissions and manual installations. Review collected by and hosted on G2.com.

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

I use Apache Airflow for project flow management and task scheduling. It's a tool that simplifies developing and designing process flows with its web-based UI and Python scripting, which I find user-friendly and effective for writing complex flow charts. Review collected by and hosted on G2.com.

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Validated ReviewerIncentivizedSource: G2 invite

 ![Bikash s.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Bikash s.")
BS

Bikash s.

DevOps Engineer

Enterprise (\> 1000 emp.)

8/2/2025

"Streamlining Data Pipelines with Apache Airflow"

4/5

What do you like best about Apache Airflow?

What I like best about Apache Airflow is its flexibility and powerful scheduling capabilities. As a developer, I can design complex workflows as code using Python, making it easy to version-control and collaborate with teammates. The UI is intuitive for monitoring DAG runs and troubleshooting issues, and Airflow’s large ecosystem of integrations lets me connect with almost any tool or database Review collected by and hosted on G2.com.

What do you dislike about Apache Airflow?

The learning curve is pretty steep, particularly when configuring the scheduler and managing task dependencies. Sometimes Airflow’s web UI feels sluggish, and troubleshooting issues can get complicated with complex DAGs. Also, while there are a lot of integrations, keeping dependencies compatible during upgrades isn’t always smooth. Review collected by and hosted on G2.com.

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

Apache Airflow solves the challenge of orchestrating and automating complex data workflows. Before Airflow, I had to manage ETL pipelines as messy scripts or manual cron jobs, which made them hard to maintain, debug, or scale. With Airflow, I define my workflows as code (DAGs), so the logic is modular, testable, and much easier to monitor or fix if something goes wrong. This means faster development, better reliability, and less time spent on repetitive maintenance. Review collected by and hosted on G2.com.

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Current UserValidated ReviewerSource: Organic

 ![Saketh K.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Saketh K.")
SK

Saketh K.

Data Engineer

Enterprise (\> 1000 emp.)

7/25/2025

"Airflow vs Cron: When Simplicity Matters"

3.5/5

What do you like best about Apache Airflow?

Opensource, UI to track almost every aspect of each job, python friendly. Review collected by and hosted on G2.com.

What do you dislike about Apache Airflow?

While Apache Airflow is powerful, it often complicates simple tasks with added abstractions like custom directives and inter-task communication. Job scheduling isn’t intuitive—requiring attention to interval ends—and log loading can be sluggish. Though opinions may vary, I personally find traditional cronjobs a simpler and more effective solution for managing a large number of jobs. Review collected by and hosted on G2.com.

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

To manage multiple jobs, track them, see the failed jobs, re-run the failed jobs, analyzing the logs to check why a job has failed - everything using Airflow UI. One of my teammates wanted us to try Airflow if it can manage our production jobs, it did, but at a higher than expected cost: infra on cloud + human hours. Review collected by and hosted on G2.com.

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Current UserValidated ReviewerIncentivizedSource: G2 invite

 ![Tobias S.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Tobias S.")
TS

Tobias S.

Sr. BI Manager

Mid-Market (51-1000 emp.)

10/15/2025

"Great DAG Frontend, But Feels Outdated"

3.5/5

What do you like best about Apache Airflow?

It has a nice user interface for viewing the status of DAGs, which has become an industry standard. Additionally, when jobs fail, the logs are very helpful for tracking down what went wrong. Review collected by and hosted on G2.com.

What do you dislike about Apache Airflow?

The setups feel outdated and unnecessarily complex. In comparison, tools such as dbt, and especially Databricks, have made significant improvements recently. Review collected by and hosted on G2.com.

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

ETL Orchestrations are essential for managing and automating data workflows. They help streamline the process of extracting, transforming, and loading data, making it easier to handle complex data pipelines. Review collected by and hosted on G2.com.

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Our network of Icons are G2 members who are recognized for their outstanding contributions and commitment to helping others through their expertise.G2 IconCurrent UserValidated ReviewerIncentivizedSource: G2 invite

 ![Verified User in Financial Services](/assets/icons/anonymous-avatar-purple-4ae1032bdb50ee5682003170c8184aee790d25958bd397abbd384ba52c596a7b.svg "Verified User in Financial Services")
IF

Verified User in Financial Services

Small-Business (50 or fewer emp.)

8/11/2025

"Streamlining Complex Data Pipelines with Ease"

4/5

What do you like best about Apache Airflow?

What I like best about Apache Airflow is its ability to orchestrate complex workflows with clear visibility and control. The DAG-based structure makes it easy to design, monitor, and modify data pipelines, while the scheduler ensures tasks run reliably and in the right sequence. Its modularity and integration capabilities with various data sources and tools make it extremely versatile. The web UI is also a huge plus, as it provides real-time monitoring and quick debugging, which saves time during development and production. Review collected by and hosted on G2.com.

What do you dislike about Apache Airflow?

While Apache Airflow is powerful, it does come with a steep learning curve for beginners, especially when setting up and configuring it for the first time. Deployments can be complex, and managing dependencies across environments requires careful attention. Additionally, for smaller projects, the overhead of running and maintaining Airflow can feel heavier compared to lightweight alternatives. Review collected by and hosted on G2.com.

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

Apache Airflow helps us automate, schedule, and monitor complex data workflows, reducing manual intervention and minimizing errors in data processing. It enables reliable orchestration of ETL pipelines, ensuring data arrives on time for analytics and reporting. This has improved operational efficiency, reduced downtime, and provided greater transparency through real-time monitoring. Given the community’s active development and focus on scalability, I believe Airflow is headed in the right direction, with ongoing enhancements that make it more user-friendly and robust for large-scale data environments. Review collected by and hosted on G2.com.

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Current UserValidated ReviewerIncentivizedSource: G2 invite

 ![Mohammad M.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Mohammad M.")
MM

Mohammad M.

Senior System Engineer

Enterprise (\> 1000 emp.)

8/11/2025

"Using Apache Airflow to orchestrate pipeline workflow for Databricks and EMR jobs"

4/5

What do you like best about Apache Airflow?

Very easy to understand and use

It is very good for defining complex workflows as code

has very good monitoring/observability features

Best part is we don't have to manage any infra if we use services like AWS MWAA for apache airflow. Very easy to implement.

Has good customer support via email or support tickets

We use it day in day out few projects for managing workflow for bedrock for using AI integrations, databricks and emr.

We use it along with AWS S3, Bedrock and Postgres SQL and Github Review collected by and hosted on G2.com.

What do you dislike about Apache Airflow?

It doesn't have any tracking mechanism and makes it hard to track any changes made or revert back a version of code

Doesn't support live streaming processing Review collected by and hosted on G2.com.

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

We use it to automate RAG workflow which retrieve information from our database and send it to bedrock knowledge base for input processing and generating output.

We also use it as orchestrator for pulling and pushing data from and to Databricks and EMR. While using S3 as storage. Review collected by and hosted on G2.com.

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Validated ReviewerIncentivizedSource: G2 invite

 ![Sarthak M.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Sarthak M.")
SM

Sarthak M.

Business Technology Solutions Associate Consultant

Enterprise (\> 1000 emp.)

7/26/2025

"Apache Airflow is a great tool"

4/5

What do you like best about Apache Airflow?

Apache Airflow makes managing complicated data tasks much easier being able to code workflows in Python is great, and the UI helps me spot issues fast. Love how it connects with everything and the built-in tools save time. Review collected by and hosted on G2.com.

What do you dislike about Apache Airflow?

Advanced setup (scaling, security) can be tricky

The UI gets cluttered with too many workflows Review collected by and hosted on G2.com.

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

Apache Airflow has been a game-changer for orchestrating our complex data pipelines. I appreciate how it enables me to automate, schedule, and monitor workflows with ease. Review collected by and hosted on G2.com.

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Current UserValidated ReviewerIncentivizedSource: G2 invite

 ![Verified User in Information Technology and Services](/assets/icons/anonymous-avatar-purple-4ae1032bdb50ee5682003170c8184aee790d25958bd397abbd384ba52c596a7b.svg "Verified User in Information Technology and Services")
II

Verified User in Information Technology and Services

Small-Business (50 or fewer emp.)

8/11/2025

"Powerful Workflow Orchestration, but Needs a Bit of Setup Effort"

3.5/5

What do you like best about Apache Airflow?

The best thing about Apache Airflow is its flexibility and scalability in orchestrating complex workflows. Review collected by and hosted on G2.com.

What do you dislike about Apache Airflow?

A common dislike about Apache Airflow is that it has a steep learning curve and requires significant setup and maintenance for production use. It takes time to master it Review collected by and hosted on G2.com.

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

It solves the problem of managing, scheduling, and monitoring complex, multi-step workflows. It benefits me in so many ways-

1. Automates repetitive processes so you don’t have to run tasks manually.

2.Ensures tasks run in the correct order with built-in dependency management.

3. Makes it easy to monitor job status, get alerts on failures, and retry tasks automatically. Review collected by and hosted on G2.com.

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Validated ReviewerIncentivizedSource: G2 invite

DK

Digamber K.

Data Engineer

Mid-Market (51-1000 emp.)

6/18/2024

"Apache Airflow : A must learn orchestration tool for data geeks."

4/5

What do you like best about Apache Airflow?

Airflow provides numerous cross-platform integration with almost all the required technologies. It has vast number of features while creating DAG's. I really loved the ideas of new release wrt object storage, easily managable platform, new operators like FTP, FTPs and custom operators. UI is bit clumsy but altogether airflow is very easy to use and implement ETL pipelines. I have been using Airflow for last 1 year and the improvement they show is very promising. Review collected by and hosted on G2.com.

What do you dislike about Apache Airflow?

UI is clumsy. In order to see the task in UI I have to go back to all dags when we retrigger 2nd time. It can be better but it compensates with the feature it has. Review collected by and hosted on G2.com.

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

We are using airflow for orchestrating and managing the ETL workflow. We wanted to have a data driven behaviour which is feasible and efficient using Airflow. Airflow provides tons of integration with other latest technologies. Review collected by and hosted on G2.com.

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Current UserValidated ReviewerIncentivizedSource: G2 invite

## Questions about Apache Airflow? Ask real users or explore answers from the community

Get practical answers, real workflows, and honest pros and cons from the G2 community or share your insights.

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GU

Guest User

What is Apache Airflow used for?

0 Upvotes

0

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GU

Guest User
•
Last activity 11 months ago

What is airflow technology?

0 Upvotes

1

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## Pricing Insights

Averages based on real user reviews.

### Time to Implement

3 months

### Return on Investment

6 months

### Perceived Cost

$$$$$

[
View More Pricing Information
](https://www.g2.com/products/apache-airflow/pricing)

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##### 
##### Apache Airflow Features

Workflow Design & Integration - AI Orchestration

Dependency Management

Workflow Coordination

Multi-Provider API Connectivity

Performance Optimization & Analytics - AI Orchestration

Workflow Performance Dashboards

Workflow Reporting

Resource Utilization Monitoring

Governance & Compliance Controls - AI Orchestration

Role-Based Access Control

Audit Trail Management

Security Protocols

[
View More Features
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##### Categories on G2

[AI Orchestration](https://www.g2.com/categories/ai-orchestration)[MLOps Platforms](https://www.g2.com/categories/mlops-platforms)

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