Comparing AWS Glue vs. Apache Airflow for Data Orchestration: A Comprehensive Performance and Cost Analysis
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V6I3P109Keywords:
Data Orchestration, AWS Glue, Apache Airflow, ETL Pipelines, Cloud Computing, Cost Analysis, Performance OptimizationAbstract
Data orchestration has become a critical component of modern data engineering pipelines, with organizations facing crucial decisions between cloud-native managed services and open-source orchestration platforms. This paper presents a comprehensive comparative analysis of AWS Glue and Apache Airflow for data orchestration, examining performance metrics, cost implications, scalability considerations, and real-world implementation outcomes. Through analysis of quantitative data from multiple enterprise implementations, we demonstrate that while AWS Glue offers superior ease of deployment and automatic scaling, Apache Airflow provides significant cost advantages (up to 96% reduction in operational expenses) and greater flexibility for complex workflow orchestration. Our findings indicate that Apache Airflow achieved 50% pipeline failure reduction and 91% manual intervention reduction compared to traditional approaches, while AWS Glue excels in rapid deployment scenarios with 30% operational cost reduction through its serverless architecture. The study provides decision-making frameworks for organizations selecting optimal data orchestration solutions based on technical requirements, cost constraints, and operational capabilities
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