Batch processing vs. stream processing by example

Batch processing and stream processing are two distinct approaches to data processing, differing in when the data is processed. Batch processing involves collecting data over time and processing it in large chunks at scheduled intervals, often ideal for handling large volumes of data where immediate results are not critical. In contrast, stream processing handles each data item in real-time as it arrives, suitable for scenarios requiring immediate data processing and analysis. The choice between batch and stream processing depends on the specific use case, with batch processing traditionally used for handling large volumes of data and stream processing used for real-time applications. Various technologies, including message brokers, streaming frameworks, and streaming databases, have emerged to support both approaches.