Batch or Stream Processing: Choosing Based on Whether Your Data Ends

The core question in data system design is whether the data is bounded, meaning it has a defined end, or unbounded, meaning it keeps arriving indefinitely. Batch processing collects events over a window or volume threshold and handles them together, while stream processing responds to each event as it occurs. Bounded data lets batch jobs produce complete answers, whereas unbounded data pushes streams toward providing fresh results instead. The author suggests deciding per feature by asking how quickly an event loses its value, using a music app as an example: fraud detection needs streaming, artist payouts need batch accuracy, and trending charts often benefit from both. The article notes that many real systems combine both approaches, and promotes a video course covering related tools and concepts.