IBM DataStage vs. Qlik Compose

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.

Incentivized

• Data movement
• Seamless integration of scripts and etl jobs
• Descriptive logging
• Ability to work with myriad of data assets
• Direct integration for Governance catalog

Incentivized

• Connector Stages to Snowflake on the cloud. We had some issues initially but since then had been corrected.
• Accessing tool from a browser (zero foot-print). Currently we need to either install locally or connect to a server to do ETL work.
• Diversify ways of authenticating users.

Incentivized

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.

Incentivized

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.

Incentivized

I believe that IBM generally has one of the worst and most complex assistance systems (physical and online) that exists.

Incentivized

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.

Incentivized

• Reduce development time by 65% compared with hand coding.
• Reduces ETL process maintenance times.
• Better data governance for technical and non-technical people.
• Improve time to market for initiatives that require data integration.

Incentivized