Azure Data Factory vs. Infor Cloverleaf Integration Platform

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

Web API integration, healthcare integration is best suited in Cloverleaf. It is robust. So it's perfectly well suited where infrastructure is advanced and up to date.

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

• Translation and support of all HL7 version data.
• Easy database integration.
• Debuggers while translation of data.

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

• High cost if one needs to migrate to another environment like cloud.
• Customer engagement. We are not yet fully aware of all services and capabilities Infor provides.
• Does not offer bundled deals. Each solutions is sold separately.

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

Good support for what is needed or to be resolved. They have knowledge and required information when you approach them.

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

Easy to implement. Cost effective. Less complex. Less support and maintenance required comparatively.

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

• Return wise it has a huge impact since a lot of healthcare data is integrated.
• It gives us a different option to be offered to our clients as compared with other integration engine tools.

Incentivized