Azure Data Factory vs. COZYROC

Well-suited Scenarios for Azure Data Factory (ADF): When an organization has data sources spread across on-premises databases and cloud storage solutions, I think Azure Data Factory is excellent for integrating these sources. Azure Data Factory's integration with Azure Databricks allows it to handle large-scale data transformations effectively, leveraging the power of distributed processing. For regular ETL or ELT processes that need to run at specific intervals (daily, weekly, etc.), I think Azure Data Factory's scheduling capabilities are very handy. Less Appropriate Scenarios for Azure Data Factory: Real-time Data Streaming - Azure Data Factory is primarily batch-oriented. Simple Data Copy Tasks - For straightforward data copy tasks without the need for transformation or complex workflows, in my opinion, using Azure Data Factory might be overkill; simpler tools or scripts could suffice. Advanced Data Science Workflows: While Azure Data Factory can handle data prep and transformation, in my experience, it's not designed for in-depth data science tasks. I think for advanced analytics, machine learning, or statistical modeling, integration with specialized tools would be necessary.

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[COZYROC] is a powerful tool and [extends] what you are able to do when it comes to ETL. It allows you to accomplish a lot of things that are very common now, but very difficult to implement with the out of the box functionality of SSIS.

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• It allows copying data from various types of data sources like on-premise files, Azure Database, Excel, JSON, Azure Synapse, API, etc. to the desired destination.
• We can use linked service in multiple pipeline/data load.
• It also allows the running of SSIS & SSMS packages which makes it an easy-to-use ETL & ELT tool.

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• Dynamic SOQL is very advantageous with Salesforce source task.
• Connecting to SharePoint is simple and seamless.
• Script Component Plus is also a very good task that we can do a lot through, that what we can't do with Script Task.

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• Limited source/sink (target) connectors depending on which area of Azure Data Factory you are using.
• Does not yet have parity with SSIS as far as the transforms available.

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• Smaller set of useful transform tasks than some competitors
• Upgrade process could be smoother (though similar to others in this space)

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So far product has performed as expected. We were noticing some performance issues, but they were largely Synapse related. This has led to a shift from Synapse to Databricks. Overall this has delayed our analytic platform. Once databricks becomes fully operational, Azure Data Factory will be critical to our environment and future success.

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Easy to use and easy to implement into ETL solutions with Microsoft SQL Server Integration Services.

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We have not had need to engage with Microsoft much on Azure Data Factory, but they have been responsive and helpful when needed. This being said, we have not had a major emergency or outage requiring their intervention. The score of seven is a representation that they have done well for now, but have not proved out their support for a significant issue

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Their support is fast and responsive. Their devs work on resolving the issues quickly. We usually will have a release of a fix within a few days.

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The easy integration with other Microsoft software as well as high processing speed, very flexible cost, and high level of security of Microsoft Azure products and services stack up against other similar products.

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We tested several other SSIS add-on packages as well. Only a few had DB2 support. And from those few COZYROC's support was the most responsive and helpful. They practically added the functionality we needed if it was not already there.

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• It is very useful and make things easier
• Debugging can improve
• Its better suited than other products with the same objective

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• It is my belie that I have thrown away $3.7k