Azure Batch vs. Azure Data Factory

Azure is specifically suited for businesses that work with customers that need to work with Microsoft software products. Any instances of Microsoft products or suites that require an environment test to set up would definitely benefit from this tool. As an IT support, it is relatively easy to support and use. Where this tool is not useful if a customer has no need for it.

Incentivized

In a data pipeline, you will be able to add different kinds of activities for example connect from your on-premise SFTP and move CSV files to storage accounts. As well data factory has its own data flow if you are an ETL developer who experimented with maybe you have worked with SSIS, thus, you will start quickly with this new feature of the data factory.

Incentivized

• Managing the users
• Having multiple environments
• Creating multiple groups

Incentivized

• Creating ETL and ELT workflows as well as orchestrating and monitoring pipelines without writing any code.
• Hybrid data integration is easily and agilely possible through this software.
• It has lot of various useful components

Incentivized

• The user interface, in my opinion, might need further clarification.
• Any situation where a user's password has to be reset would benefit from this feature.
• Any accounts that were accidentally established more than once may be transferred over quickly and easily.

Incentivized

• Learning curve for pipeline creation interface.
• Alerting isn't necessarily built in. Had to work around this to meet team needs.
• With GIT enabled, some features can only be done via git, while some need to be done via the portal.

Incentivized

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.

Incentivized

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

Incentivized

Both are excellent resources that successfully deliver the promised benefits. Two rival businesses, each with its own distinct culture and set of goals. As far as IT assistance goes, I find Azure's user interface to be slightly more intuitive. Both resources are valuable and have their advantages and disadvantages. Both are crucial if you run a fast-paced business with a large consumer base.

Incentivized

Azure Data Factory fits well into our overall systems architecture where we already utilize largely Azure services and also Microsoft based products in the on-premises environment. I think cost structure is also very competitive with Azure Data Factory. Most services provide a visual interface for designing ETL workflows, but our team found Azure Data Factory's interface more intuitive.

Incentivized

• After initial setup, we now have significantly less time spent processing data.
• The automation of data formatting and display after processing is exciting because it frees us to focus on the data itself.
• Since using Batch, we have significantly decreased the number of items we previously utilized.

Incentivized

• Limiting the amount of data moving up and down from the cloud for cloud-native applications.
• Overall simple to use interface which is actually easier for a first time ETL developer than SSIS.

Incentivized