Bulk data processing usually performs asynchronous due to the transitional engine capabilities. Batch processing is suitable for optimizing the execution of high-volume repetitive tasks. The mainframe batch mainly prevents parallel processing due to the mono thread model, locking I/O to data storage as its design. COBOL prevents concurrent processing, which leads to a higher Total Cost of Ownership (TCO). Practical and cost-optimized architectures are available to modernize the existing COBOL Batch to:
- Spring Batch microservices.
- Real-time Batch microservices on Cloud.
Spring Batch Microservices:
Spring Batch is designed as a lightweight, comprehensive framework to enable robust batch applications. Provides reusable functions to process large volumes of records, including features like
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