Batch processing involves processing large amounts of data in batches, whereas stream processing processes data as it becomes available, often in real-time. Kapacitor tasks can be configured to operate in either batch or stream mode, depending on the nature of the task and the type of data being processed. Stream processing is particularly useful for handling high-volume, high-velocity, and high-variance data streams, such as those found in IoT applications. Batch processing, on the other hand, is better suited for tasks that require more control over data processing, such as data aggregation or filtering. The choice between batch and stream processing ultimately depends on the specific requirements of the task and the characteristics of the data being processed. Kapacitor's flexibility allows developers to choose the approach that best fits their needs.