What is the primary distinction between batch processing and stream processing?

The primary distinction between batch processing and stream processing lies in their handling of data volumes and timing. Batch processing is designed to manage and process large volumes of data all at once, rather than in a continuous flow. This approach typically involves collecting data over a period and processing it in bulk at scheduled intervals. It is often used in scenarios where immediate processing is not critical, allowing for optimizations that can enhance performance over large datasets.

In contrast, stream processing deals with data in real-time or near-real-time as it arrives. This method is suited for environments where timely data insights are required, such as monitoring systems or real-time analytics.

The correct answer captures the essence of batch processing, signifying its capability to process substantial amounts of data collectively, which differentiates it from stream processing methods that prioritize immediate data handling.