Datastage vs Seebeyond

Post questions here relative to DataStage Enterprise/PX Edition for such areas as Parallel job design, Parallel datasets, BuildOps, Wrappers, etc.

Moderators: chulett, rschirm, roy

vyyuri
Premium Member
Premium Member
Posts: 25
Joined: Wed Jul 26, 2006 9:35 am
Location: Michigan

Post by vyyuri »

Thanks a lot every one for sharing the information . I pointed out every thing and the presentation went well . Sharing with every one what I got.

EAI ( Seebeyond, ICAN,JCAPS) : - Acronym for Enterprise Application Integration, EAI involves integration of incompatible business applications within and beyond enterprise to allow them to talk to each other seamlessly and to share data in real time

ETL(Datastage Informatica, Ab initio) : Extraction, Transformation and Loading (ETL) are three database functions that are combined into one tool to pull data out of source databases and place it into target databases

What differ are: the purpose, speed, direction and amount of data that are transformed and placed within the unified view from the external sources

Please find the differences between these two technologies ( I.e Differences between Datastage and Seebeyond)

<img src="c:\temp.bmp" alt="God is great" />

There are other factors like Cost, Licensing and the support we have needs to be considered before making the decision



Conclusion: - As per my understanding for initial load we can go for datastage . For Incremental if we want to move stuff around within Oracle, then a combination of PL/SQL scripts scheduled from SeeBeyond/JCAPS will do the trick for us



Note :- But again When, in future, because of amalgamations, mergers, the need to capture data from or write data to other sources, or whatever other reasons, then we will have difficulty doing that in PL/SQL (for example, how do you get data from Excel?). (Businesses do change over time, so an ETL tool for managing the deltas is probably your better long-term solution. The jobs created by that tool can still be externally scheduled, if required)
Ultimately, the decision is one of maintenance; in a multiple data source/target environment a more flexible ETL tool will require fewer skills to maintain than a disparate set of vendor-specific scripts.
srinivas
Post Reply