Real-Time Data Processing: Stream Processing vs Batch Processing
TL;DR Batch processes bounded data on a schedule; streaming processes unbounded data continuously - different operational profiles, not a religious choice Streaming often costs 5-10x more per row than batch for the same volume; you pay for latency Streaming earns its keep when event value decays fast: fraud, ops alerts, live dashboards, inventory sync The lambda hybrid (streaming fast path + batch system of record) is what large platforms actually run Default to batch in 2026; add streaming only where latency genuinely matters, and land raw events in object storage from day one If you spend enough time in data engineering, you will eventually encounter the conviction that batch processing is dying and streaming is the future. This is the third or fourth time the industry has had this conversation in my career, and the answer has been the same every time. Streaming is not the future. Batch is not the past. They are different tools with different operational profiles, and the systems that age well use both, with discipline about which is the right choice for which problem. ...
