IBM® DataStage® is a data integration tool that helps users to design, develop and run jobs that move and transform data. At its core, the DataStage tool supports extract, transform and load (ETL) and extract, load and transform (ELT) patterns. A basic version of the software is available for on-premises deployment, and the cloud-based DataStage for IBM Cloud Pak® for Data offers automated integration capabilities in a hybrid or multicloud environment.
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SSIS
Score 8.4 out of 10
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Microsoft's SQL Server Integration Services (SSIS) is a data integration solution.
Currently not using any of the Informatica tools, so, I don't have a real way of comparing the tools. But comparison against Microsoft SSIS (SQL Server Integration Services) I'd say DataStage stacks favorably. DataStage is a powerful tool for ETL processes that integrates …
DataStage offers better integration capabilities without the need to write code manually. It also has a native ETL engine whereas MSIS requires a SQL Server. It has better integration capabilities with data quality, data profiling and data governance tools. The main drawback of …
SSIS is a very basic, developer-oriented ETL tool and while it lacks many of the nice UX features of its competitors it is a powerful tool that comes as a part of SQL Server and, in the hands of experienced developers with domain knowledge, can meet most organizations' ETL …
Excellent Cloud data mapping tool and easy creating multiple project data analytics in real-time and the report distribution are excellent via this IBM product. Easy tool to provide data visualization and the integration is effective and helpful to migrating huge amounts of data across other platforms and different websites insights gathering.
Ideal for daily standard ETL use cases whether the data is sourced from / transferred to the native connectors (like SQL Server) or FTP. Best if the company uses MS suite of tools. There are better options in the market for chaining tasks where you want a custom flow of executions depending on the outcome of each process or if you want advanced functionality like API connections, etc.
SSIS has been a bit neglected by Microsoft and new features are slow in coming.
When importing data from flat files and Excel workbooks, changes in the data structure will cause the extracts to fail. Workarounds do exist but are not easily implemented. If your source data structure does not change or rarely changes, this negative is relatively insignificant.
While add-on third-party SSIS tools exist, there are only a small number of vendors actively supporting SSIS and license fees for production server use can be significant especially in highly-scaled environments.
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
Because it is robust, and it is being continuously improved. DS is one of the most used and recognized tools in the market. Large companies have implemented it in the first instance to develop their DW, but finding the advantages it has, they could use it for other types of projects such as migrations, application feeding, etc.
SQL Server Integration Services is a relatively nice tool but is simply not the ETL for a global, large-scale organization. With developing requirements such as NoSQL data, cloud-based tools, and extraordinarily large databases, SSIS is no longer our tool of choice.
It could load thousands of records in seconds. But in the Parallel version, you need to understand how to particionate the data. If you use the algorithms erroneously, or the functionalities that it gives for the parsing of data, the performance can fall drastically, even with few records. It is necessary to have people with experience to be able to determine which algorithm to use and understand why.
Raw performance is great. At times, depending on the machine you are using for development, the IDE can have issues. Deploying projects is very easy and the tool set they give you to monitor jobs out of the box is decent. If you do very much with it you will have to write into your projects performance tracking though.
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.
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
It's obvious since they both are from the same vendors and it makes it easier and can get better rates for licensing. Also, sales rapes are very helpful in case of escalations and critical issues.
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.
