Apache Airflow
Reviews
Star rating
Rank in MLOps Platforms
Pros and cons
Pros
- Ease of Use
- User Interface
- Flexibility
- Integrations
- Automation
- Easy Integrations
Cons
- Difficult Setup
- Learning Curve
- Steep Learning Curve
- Outdated User Interface
- Learning Difficulty
- UX Improvement
Traffic & LLM citations
Source: G2 review data
Winning from
Losing to
Key stats
Adoption by company size
| Segment | Share of reviews |
|---|---|
| Small Business | 22.8% |
| Mid-Market | 45.7% |
| Enterprise | 31.5% |
Quarterly history
| Quarter | Reviews | Star rating |
|---|---|---|
| 2025 Q1 | 1 | 4.5 |
| 2025 Q2 | 1 | 5.0 |
| 2025 Q3 | 23 | 4.5 |
| 2025 Q4 | 6 | 4.4 |
| 2026 Q1 | 5 | 4.6 |
| 2026 Q2 | 5 | 4.8 |
| 2026 Q3 | 2 | 5.0 |
Satisfaction ratings
What reviewers say
Flexible Workflow Management with Apache Airflow
“What I like best about Apache Airflow is its flexibility in building and managing complex workflows using code. The DAG-based approach makes it easy to define dependencies, schedule jobs, and monitor pipeline execution in a centralized way.”
Scalable Workflows with Apache Airflow, Best data Engineering tool for Orchestrator,Easy Deployment
“It is easiy to deploy with docker. Provide secure authentication. A better UI in airlfow3.x. There. is many method, operator, hooks are added. easily to add dependecy. A better workflow monitoring tool. Easily schedule , activate and deactivate jobs. Good performance when used in”
Streamlined ETL with Powerful DAG Visualization
“I love using Apache Airflow for creating ETL pipelines, especially with its UI-driven DAG visualization that makes understanding the workflow and dependencies so much easier. The graph and stage view are amazing, and identifying errors is straightforward. The task monitoring feat”