This document discusses whether it is better to process data using a stream or batch approach. It describes how one company evolved their data pipeline from a micro-batch streaming process to a batch approach. The streaming process was very expensive, costing $400,000 per year to run. It also had issues with wasted resources during idle times, slow processing during bursts of data, and long recovery times from outages. The company rearchitected the process to use discrete time windows run in isolated batch jobs. This new batch approach reduced costs by 60% to $160,000 per year and improved processing efficiency and outage recovery times.