January 31, 2019


Anonymous | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User

Overall Satisfaction with IBM InfoSphere DataStage

  • DS is one of the most powerful ETL tools on the market. Its connectors to different bases plus the pack make it a solid tool, and complete. It has a great number of functions, and the work with a big amount of data with DS is not complex (as long as you have the knowledge and know how to handle the partitioning algorithms, etc).
  • DataStage has improved over time. It has improved its connectors, added functionalities, making easier the programming and the maintenance of the development.
  • Connectivity.
  • Handling large numbers of records.
  • Varied partitioning algorithms.
  • Complementary packages of connectivity to applications, SAP, etc.
  • You must understand and know the algorithms, since the wrong use of them generates more time in processing.
  • Metadata. You need to develop with connectors, and taking all the Metadata from the menu, all the data that you complete manually, you can't track it.
  • The connection with SAP has allowed us to extract useful data, allowing us to set aside costly processes such as ABAP, etc.
  • DataStage can load data wherever the data is . This gives you the facility to integrate data, create a DW with all the integrity that you need.
Compared to other ETL tools, the connectors really work, and makes the developments less complex because they facilitate the development of the processes. The maintenance of the processes is simple, since it is a very visual tool, and you can count on the technical documentation given by the tool.
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.
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.
Recommend for:
Small and large data volumes
For development and processing of complex data (functions / routines)
File management
Migrating Data from a Database to other
When you need to track all the data loaded, because you can have all the information about the transformation, the derivation, and where it was used

IBM InfoSphere DataStage Feature Ratings

Connect to traditional data sources
Connecto to Big Data and NoSQL
Simple transformations
Complex transformations
Data model creation
Metadata management
Business rules and workflow
Testing and debugging
Integration with data quality tools
Integration with MDM tools