Loading Methods: Full Loading vs. Incremental Loading

Another consideration regarding the loading method to the destination repository is whether to use full, incremental, or hybrid loading.

• Full load: A full load is when all of the data from a source is loaded into a target. This is the simplest method to implement, but it can be time-consuming and inefficient if the data set is large.   

• Incremental load: An incremental load is when only the data that has changed since the last load is loaded into the target. This is more efficient than a full load but can be more complex to implement.

• Hybrid load: This method is a combination of full and incremental loads. It starts with a full load, and then subsequent loads are incremental. This can be a good option if the data set is large and changes frequently.

The best method for loading data into an ETL pipeline depends on the specific needs of the project.
If the dataset is large and changes frequently, an incremental or hybrid load might be a better option.