Incremental processing involves processing the entire dataset from scratch in each run to ensure data accuracy, which may increase costs but guarantees up-to-date information.

Incremental processing is a technique where only the new or changed data since the last processing run is processed, significantly reducing the amount of data handled and thus lowering costs and improving performance.

Incremental processing requires the use of real-time data streaming technologies to process data as it arrives, which may not always be cost-effective for all types of data pipelines.

Incremental processing can be implemented by tracking changes in the data source, such as using timestamps or change data capture (CDC), to identify and process only the delta, optimizing both cost and performance.