Apache Airflow vs. Cloudera
A side-by-side comparison based on G2 review data.
| Metric | Apache Airflow | Cloudera |
|---|---|---|
| Overall rating | 4.4 | 4.2 |
| Review count | 130 | 205 |
| Ease of use | 8.7 | 8.6 |
| Ease of setup | 8.2 | 8.4 |
| Quality of support | 8.5 | 8.4 |
| Meets requirements | 9.2 | 8.9 |
| NPS | 62.5 | 45.641026 |
| Small Business | 22.8% | 34.3% |
| Mid-Market | 45.7% | 27.5% |
| Enterprise | 31.5% | 38.2% |
| Total page views | 451 | 964 |
| Total LLM citations | 1,881 | 1,693 |
Apache Airflow
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.
- Ease of Use
- User Interface
- Flexibility
- Integrations
- Automation
- Easy Integrations
Cloudera
Cloudera is the only hybrid data and AI platform company that large organizations trust to bring AI to their data anywhere it lives. Unlike other providers, Cloudera delivers a consistent cloud experience that converges public clouds, on-prem data centers, and the edge, leveraging a proven open-source foundation. As the pioneer in big data, Cloudera empowers businesses to apply AI and assert control over 100% of their data, in all forms, improving security, governance, and real-time and predictive insights.
- Ease of Use
- Scalability
- Security
- Features
- Performance
- Data Management