DataStage is actually two separate things.
In production (and, of course, in development and test environments) DataStage is just another application on the server, an application which connects to data sources and targets and processes ("transforms") the data as they move through the application. Therefore DataStage is classed as an "ETL tool", the initials standing for extract, transform and load respectively. DataStage "jobs", as they are known, can execute on a single server or on multiple machines in a cluster or grid environment. Like all applications, DataStage jobs consume resources: CPU, memory, disk space, I/O bandwidth and network bandwidth.
DataStage also has a set of Windows-based graphical tools that allow ETL processes to be designed, the metadata associated with them managed, and the ETL processes monitored. These client tools connect to the DataStage server because all of the design information and metadata are stored on the server.
In production (and, of course, in development and test environments) DataStage is just another application on the server, an application which connects to data sources and targets and processes ("transforms") the data as they move through the application. Therefore DataStage is classed as an "ETL tool", the initials standing for extract, transform and load respectively. DataStage "jobs", as they are known, can execute on a single server or on multiple machines in a cluster or grid environment. Like all applications, DataStage jobs consume resources: CPU, memory, disk space, I/O bandwidth and network bandwidth.
DataStage also has a set of Windows-based graphical tools that allow ETL processes to be designed, the metadata associated with them managed, and the ETL processes monitored. These client tools connect to the DataStage server because all of the design information and metadata are stored on the server.
