DataStage is an ETL tool that extracts data, transforms and loads data from source to the target.
DataStage facilitates business analysis by providing quality data to help in gaining business intelligence.
Informatica is used for Data integration in ETL
Informatica offers the capability to connect & fetch data from different heterogeneous sources and processing of data.
These are the major differences between Informatica and DataStage, you can select the relevant tool based on the requirement:
Multiple Partitions: Informatica offers partitioning as dynamic partitioning which defaults a workflow, not at every Stage. It also offers other partitioning choices as well at the workflow level. Whereas, DataStage offers 7 different types of multi-processing partitions.
User Interface: Informatica offers access to the development and monitoring effort through its 4 GUIs – offered as Informatica PowerDesigner, Repository Manager, WorkflowDesigner, Workflow Manager. Whereas, DataStage caters to development and monitoring its jobs through 3 GUIs – IBM DataStage Designer(for development), Job Sequence Designer(workflow design) and Director(for monitoring).
Type of Link: To link two components in Informatica, link at the column level and connect each and every column between the two components. While, In DataStage, link at the component level, and then map individual columns. This allows coding templates that are all linked up – just add columns.
Reusability: Informatica offers ease of re-usability through Mapplets and Worklets for re-using mappings and workflows. This really improves the performance. DataStage offers the re-usability of a job through containers(local shared). Make a copy, compile and run to reuse a Job Sequence(workflow).
Heterogeneous Sources: In Informatica, both heterogeneous sources and homogenous sources are used. While DataStage does not perform very well with heterogeneous sources and might end up extracting data from all the sources and putting them into a hash and start your transformation
Code Generation and Compilation: Informatica’s thrust is the auto-generated code. A mapping gets created by dropping a source-transformation-target that doesn’t need to be compiled. Whereas, DataStage requires you to compile a job in order to run it successfully.
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