IBM DataStage vs. Vertify

DataStage is somewhat outdated for an ETL. I guess that's what makes it a bit lagged behind its competitors. It can be used for data processing, sure, but its performance seems to be lagging behind or quite slow given the server it is running from. I won’t depend on this application if it's handling a lot of mission-critical banking and business data.

I would recommend it, as VertifyData exactly fit our use case. I can't speak for all use cases and all connectors - naturally - but the ones we are using and have explored so far, work perfectly well. Also, being a person myself that is not fluent in SQL or JSON or API language in general, I was still able to create all workflows our company needed myself. Which I consider a huge benefit.

• Connect to multiple types of data-sources including Oracle, Teradata, Snowflake, SQl Server.
• Powerful tool to load large volumes of data.
• Transformation stages allow us to reduce the amount of code needed to create ETL scripts.
• Allow us to synchronize and refresh data as much as needed.

Incentivized

• Communication.
• Follow up.
• They're constantly trying to improve.

• Technical support is a key area IBM should improve for this product. Sometimes our case is assigned to a support engineer and he has no idea of the product or services.
• Provide custom reports for datastage jobs and performance such as job history reports, warning messages or error messages.
• Make it fully compatible with Oracle and users can direct use of Oracle ODBC drivers instead of Data Direct driver. Same for SQL server.

Incentivized

• Automated error trouble-shooting is not always clear/helpful
• Clearly distinguishing internal errors vs. external errors
• Perhaps a blog where users can interact with questions + solutions

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

Creating a mapping between source and target while also using lookups and transformations is not trivial. And VertifyData solved this reasonably well, at least all users in my organization understood it pretty quickly.

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

It is not the easiest user interface to read/understand. However, once you understand how it works, then using it is not that bad. It's hard to remember what feature is listed under what tab (Manage vs. Define). A suggestion would be to get all call to actions on the same page

IBM offers different levels of support but in my experience being and IBM shop helps to get direct support from more knowledgeable technicians from IBM. Not sure on the cost of having this kind of support, but I know there's also general support and community blogs and websites on the Internet make it easy to troubleshoot issues whenever there's need for that.

Incentivized

With effective capabilities and easy to manipulate the features and easy to produce accurate data analytics and the Cloud services Automation, this IBM platform is more reliable and easy to document management. The features on this platform are equipped with excellent big data management and easy to provide accurate data analytics.

Incentivized

Vertify offered more flexibility and was presented as a simple solution. In reality, it is more complex that we envisioned and we have never fully utilized our tools due to the lack of ability to configure things properly.

Incentivized

• It’s hard to say at this point, it delivers, but not quite as I expected. It takes a lot of resources to manage and sort this out (manpower, financial).
• Definitely, I don’t have the exact numbers, but given the data it processes, it is A LOT. So props to the developer of this application.
• Again, based on my experience, I’d choose other ETL apps if there is one that's more user-friendly.

• Independently, teams are able to carry out their process with less communication and at a higher level of accuracy.
• VertifyData is actively taking into consideration, consulting, and supporting our plans to build out the business