When do we use a parallel job and a server job?

Data Science, AI and ML
#1

The decision to use a parallel task or a server job is based on the processing requirements, functionality, implementation time, and cost. The server task typically runs on a single node, using a DataStage Server Engine, and deals with modest amounts of data. The parallel task is distributed across several nodes and operates on a DataStage Parallel Engine, handling enormous amounts of data.