Alooma vs. IBM DataStage

Very appropriate for managing an ELT stack -- Alooma handles the 'E' and 'L' pieces very well. Due to the way transformation is setup, it is more on the lightweight side of things and thus works for this kind of stack. For more traditional ETL stacks, Alooma would probably not be the right fit.

Incentivized

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

• Transformation of data before entering the data warehouse -- allows for a consistent/understandable schema for analytics teams.
• Adding of additional data sources: Alooma has a large library of pre-built, common 3rd party vendors for which data is often needed to be ETL-ed.

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

• More tools on managing the data warehouse itself. Although great on the ingest and transformation of data, more help provided by the tool on managing the outputs would be welcome.
• Increase possibilities in the transformation step, rather than single event transformations.

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

Haven't used the alternatives, since Alooma was one of the earlier ones to the market. From a cursory viewing, however, the features seem to match relatively similarly.

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

• Allowing for additional data sources to more automation capability around monitoring the business is a huge ROI

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