Coupler.io vs. IBM DataStage

Exporting data from one platform to sheets or Looker Studio or excel.

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DataStage is somewhat outdated for an ETL.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.

• Syncing data from multiple sources into one destination
• Quick setup and connection to accounts
• Transforming data during the sync process (allows you to create new formula-based fields based on source data)

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• 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.

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• More options for triggering a sync (currently scheduled or manual)
• Additional data sources

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• 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.

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It's amazing thing for marketers. Reduces technical workload, speeds up reporting.

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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.

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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.

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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.

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It's easy to use and easily configurable. Also, offers a lot of connectors.

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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.

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• Saving time on manual data syncing allows our team to focus on more substantive work
• Knowing that data is consistently updated takes guesswork out trying to figure out whether or not things are up-to-date

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• 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.