The State of Apache Airflow. An Astronomer Report.

How is your company unlocking the potential of its data? In a time when digital innovation shapes every aspect of business, data is not just valuable—it’s the lifeblood of innovation and growth. But collecting data is just the start.

The true strength stems from adopting a data-driven strategy, with data orchestration comprising its central nervous system. Seamless data integration and movement across varied teams have become essential for gaining a competitive advantage, determining whether a company is a market leader or follower.

Apache Airflow is at the forefront of this transformation, tackling the complexities of data scalability and data orchestration head-on. It has become an essential component of the technology stack for teams pushing the boundaries in AI/ML and data pipeline delivery.

Explore the insights from the 2024 State of Apache Airflow report, which offers a detailed analysis of how Airflow is shaping data delivery trends, fostering community growth, and transforming organizational data strategies.

Trend 1

Apache Airflow: A Year of Unprecedented Growth

In 2023, Apache Airflow experienced remarkable growth, evidenced by a spike in downloads, an active contributor community, and a notable rise in GitHub stars. Additionally, an impressive 92% of users stated they would recommend Airflow, showcasing its widespread approval and satisfaction within the user community.

Trend 2

Companies Rely on Apache Airflow for Mission-Critical Data Delivery

Embedded into daily (55%) and weekly (26%) routines of organizations, Apache Airflow is foundational for mission-critical data operations. The reliance on Airflow, paired with the severe consequences of downtime, highlights its critical role in modern business architectures. Companies depend on Airflow not just for effective data delivery but also as a key safeguard against disruptions that threaten operational integrity and profitability.

The data emphasizes the vital role of Apache Airflow for businesses: 46% indicate that any problems with Airflow can halt their entire operation, 36% note impacts on several teams, and 13% acknowledge its importance specifically to their team. Overall, 95% of users depend on Airflow for operational efficiency.

Impacts from data pipeline disruptions are felt widely, with 72% noting significant effects on internal systems, team productivity, and revenue. It’s evident that Airflow is integral to maintaining operational continuity and efficiency.

Expanding Use Cases: The Versatility of Airflow

82% of teams have reported a broader application of Airflow, moving beyond its initial scope, with 44% experiencing a substantial expansion into new areas. This signals growing trust in Airflow to drive efficiency and innovation, meeting the diverse and evolving needs of businesses across sectors. Its application ranges from traditional data management to innovative new applications.

Trend 3

Apache Airflow: Setting The New Standard for ML/AI Pipelines

As ML and AI drive technological progress, Airflow has become essential for addressing development and deployment obstacles. Its efficiency in streamlining processes, improving standardization, and managing compliance complexities have made it a preferred tool for ML/AI pipeline development.

Airflow is most commonly used for data ingestion and ETL/ELT tasks in analytics (90%) and business operations (67%). However, its role in MLOps is expanding, now representing 28% of its usage.

This trend underlines Airflow’s growing role in ML/AI development workflows. Almost 30% of organizations using Airflow are focusing on AI initiatives, evidenced by a 24% year-over-year growth in ML and AI projects facilitated by Airflow. Businesses are recognizing that the extensive features and benefits of Airflow allow for its application in a wider range of tasks, moving from traditional to more advanced AI/ML applications

Advancing ML/AI Innovation with Airflow

As businesses navigate the growth of AI, they face obstacles such as isolated tools, limited teamwork, and regulatory challenges. Astronomer, powered by Apache Airflow, tackles these issues by:

• Unify and standardize development practices for production-ready AI
• Support next-generation applications with unmatched compute power
• Ensure AI trustworthiness with data lineage
• Accelerate AI development with seamless integrations

Astronomer and the Impact on Apache Airflow and Its Community

Through strategic initiatives, Astronomer has streamlined the adoption and enhancement of Apache Airflow, making it more accessible for both individuals and teams. This leadership has nurtured a thriving community where data practitioners from around the world can learn, collaborate, and advance their skills.

Maximizing Business Potential with Airflow

The increasing impact of Airflow and its ability to meet the complex demands of modern businesses underline the considerable advantages of integrating Airflow to your data workflows. Making the decision to adopt Airflow can be a key step in improving your data orchestration and taking full advantage of ML/AI innovations. Now is the time to explore how Airflow can strengthen your organization’s data management strategy and enhance operational performance.