Can you tell the difference between a full load and an incremental load?

In ETL, a full load copies all data from the source to the target, regardless of changes. It is simple to implement but can be resource‑intensive and may cause downtime if the dataset is large. An incremental load, on the other hand, transfers only the data that has changed since the last load, using techniques such as change data capture, timestamp columns, or log‑based replication. Incremental loads reduce network traffic, processing time, and storage writes, but they require reliable change tracking mechanisms. For example, when migrating a sales table, a full load would copy every row each time, while an incremental load would copy only rows with a newer timestamp or a flag indicating modification. Full loads are typically used for initial data loads or when the schema changes, whereas incremental loads are used for ongoing synchronization. The choice depends on data volume, change frequency, and system constraints.