Different kinds of Copy behavior in ADF

Azure Data Factory (ADF) is a cloud-based data integration service provided by Microsoft. It allows users to create, schedule, and manage data pipelines that move and transform data from various sources and destinations. A key component of ADF is the ability to copy data from one location to another. In this blog, we will explore the different copy behaviors available in Azure Data Factory.

1. Full Load Behavior The Full Load Behavior is the default behavior of the copy activity. It is used when the source and destination data stores are not synchronized, and the entire data set needs to be copied from the source to the destination. In this behavior, the copy activity reads all the data from the source and writes it to the destination, overwriting any existing data in the destination.
2. Incremental Load Behavior The Incremental Load Behavior is used when only the new or changed data needs to be copied from the source to the destination. This behavior is useful when the source and destination data stores are regularly synchronized, and the data changes frequently. In this behavior, the copy activity reads only the new or changed data from the source and writes it to the destination.
3. Merge Behavior The Merge Behavior is used when the source and destination data stores have overlapping data, and the goal is to merge the data sets. In this behavior, the copy activity reads the data from the source and the destination and merges them based on a specified key column. The merge behavior can be configured to insert new rows, update existing rows, or delete rows that no longer exist in the source data store.
4. Append Behavior The Append Behavior is used when the data needs to be added to an existing data set in the destination data store. In this behavior, the copy activity reads the data from the source and appends it to the existing data in the destination. This behavior is useful when the source data set is too large to load into memory or when the data set is too large to be processed in a single pass.
5. Upsert Behavior The Upsert Behavior is used when the source and destination data stores have overlapping data, and the goal is to insert new rows and update existing rows. In this behavior, the copy activity reads the data from the source and updates the existing rows in the destination based on a specified key column. If a row does not exist in the destination, it is inserted. This behavior is useful when the data is changing frequently, and the goal is to keep the data stores in sync.

In conclusion, Azure Data Factory provides various copy behaviors to meet different data integration requirements. By understanding these behaviors, users can select the appropriate behavior for their use case and optimize their data integration pipelines.