Unified Workflow Containers for Managing Batch and Streaming ETL Processes in Enterprise Data Engineering
Keywords:
unified ETL, workflow containers, batch–stream unification, data engineering architectureAbstract
Unified workflow containers establish a coherent execution framework for handling batch,
streaming, and hybrid ETL processes within a single operational model, reducing the fragmentation
traditionally seen in enterprise data engineering ecosystems. By combining container-level isolation with
centralized metadata synchronization and adaptive scheduling, the approach delivers more predictable
performance, stronger lineage transparency, and greater runtime stability across diverse workloads. The
evaluation confirms that these pre-2019 architectural principles already embodied the foundations of modern
unified data platforms, enabling smoother recovery, improved data freshness, and more consistent system
behavior under fluctuating load conditions. As data volumes and real-time processing demands continue to
grow, unified workflow containers provide a resilient and forward-compatible architecture for building
scalable, high-efficiency ETL infrastructures.
