IBM InfoSphere Information Server vs. SQL Server Integration Services

Information Server is extremely useful to replace manual developments that require a lot of coding effort. It significantly increases the productivity of the initial development and the future maintenance of the processes since it has a visual development environment with self-documentation.

Ideal if the company is already a Microsoft shop, so chances are that it is free with SQL Server. Also, good for moving data between on premise systems. Not ideal for moving data to the cloud. No functionality out of the box to work with REST APIs. Stable product but definitely not the future

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• IIS best for ETL ,not ELT , and many and diffrent source systems.
• It also can process big data , unstuctured data
• It is not only DWH , you can use infosphere for analys and see the bigger architecture of your OLTP systems

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• Standard ETL use cases for daily loads
• Loading incoming data from Vendors which is placed on FTP and adding them to the SQL Warehouse
• Creating outgoing data files and writing them to Vendor FTPs
• Easy Active Directory integration for seamless connections to SQL Server
• CI/CD by hosting the code on visualstudio.com

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• I would be nice to have a new web development environment for DataStage.
• Connectivity Packs such as Pack for SAP Application are a little pricey.
• It is confusing for new developers the possibility of developing jobs using different execution engines such as Parallel or Server.

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• Connection managers for online data sources can be tricky to configure.
• Performance tuning is an art form and trialing different data flow task options can be cumbersome. SSIS can do a better job of providing performance data including historical for monitoring.
• Mapping destination using OLE DB command is difficult as destination columns are unnamed.
• Excel or flat file connections are limited by version and type.

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• Scale of implementation
• IBM techsupport

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Some features should be revised or improved, some tools (using it with Visual Studio) of the toolbox should be less schematic and somewhat more flexible. Using for example, the CSV data import is still very old-fashioned and if the data format changes it requires a bit of manual labor to accept the new data structure

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SSIS is a great tool for most ETL needs. It has the 90% (or more) use cases covered and even in many of the use cases where it is not ideal SSIS can be extended via a .NET language to do the job well in a supportable way for almost any performance workload.

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SQL Server Integration Services performance is dependent directly upon the resources provided to the system. In our environment, we allocated 6 nodes of 4 CPUs, 64GB each, running in parallel. Unfortunately, we had to ramp-up to such a robust environment to get the performance to where we needed it. Most of the reports are completed in a reasonable timeframe. However, in the case of slow running reports, it is often difficult if not impossible to cancel the report without killing the report instance or stopping the service.

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The support, when necessary, is excellent. But beyond that, it is very rarely necessary because the user community is so large, vibrant and knowledgable, a simple Google query or forum question can answer almost everything you want to know. You can also get prewritten script tasks with a variety of functionality that saves a lot of time.

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The implementation may be different in each case, it is important to properly analyze all the existing infrastructure to understand the kind of work needed, the type of software used and the compatibility between these, the features that you want to exploit, to understand what is possible and which ones require integration with third-party tools

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DataStage is more robust and stable than ODI The ability to perform complex transformations or implement business rules is much more developed in DS

I had nothing to do with the choice or install. I assume it was made because it's easy to integrate with our SQL Server environment and free. I'm not sure of any other enterprise level solution that would solve this problem, but I would likely have approached it with traditional scripting. Comparably free, but my own familiarity with trad scripts would be my final deciding factor. Perhaps with some further training on SSIS I would have a different answer.

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• Productivity of the development of integration processes.
• Better documentation and governance.
• Reduce training costs of various technologies.

• Data integrity across various products allows unify certain processes inside the organization and save funds by reducing human labour factor.
• Automated data unification allows us plan our inputs better and reduce over-warehousing by overbuying
• The employee number, responsible for data management was reduced from 4 to 1 person

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