We performed a comparison between Azure Data Factory and CloverETL based on real PeerSpot user reviews.
Find out what your peers are saying about Microsoft, Informatica, Oracle and others in Data Integration."I can do everything I want with SSIS and Azure Data Factory."
"The most valuable features are data transformations."
"The trigger scheduling options are decently robust."
"Its integrability with the rest of the activities on Azure is most valuable."
"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."
"The function of the solution is great."
"For me, it was that there are dedicated connectors for different targets or sources, different data sources. For example, there is direct connector to Salesforce, Oracle Service Cloud, etcetera, and that was really helpful."
"It's cloud-based, allowing multiple users to easily access the solution from the office or remote locations. I like that we can set up the security protocols for IP addresses, like allow lists. It's a pretty user-friendly product as well. The interface and build environment where you create pipelines are easy to use. It's straightforward to manage the digital transformation pipelines we build."
"No dependence on native language and ease of use."
"Connectivity to various data sources: The ability to extract data from different data sources gives greater flexibility."
"Server features for scheduler: It is very easy to schedule jobs and monitor them. The interface is easy to use."
"Key features include wealth of pre-defined components; all components are customizable; descriptive logging, especially for error messages."
"I rate Azure Data Factory six out of 10 for stability. ADF is stable now, but we had problems recently with indexing on an SQL database. It's slow when dealing with a huge volume of data. It depends on whether the database is configured as general purpose or hyperscale."
"We require Azure Data Factory to be able to connect to Google Analytics."
"It does not appear to be as rich as other ETL tools. It has very limited capabilities."
"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."
"This solution is currently only useful for basic data movement and file extractions, which we would like to see developed to handle more complex data transformations."
"It can improve from the perspective of active logging. It can provide active logging information."
"On the UI side, they could make it a little more intuitive in terms of how to add the radius components. Somebody who has been working with tools like Informatica or DataStage gets very used to how the UI looks and feels."
"User-friendliness and user effectiveness are unquestionably important, and it may be a good option here to improve the user experience. However, I believe that more and more sophisticated monitoring would be beneficial."
"Resource management: We typically run out of heap space, and even the allocation of high heap space does not seem to be enough."
"Its documentation could be improved."
"Needs: easier automated failure recovery; more, and more intuitive auto-generated/filled-in code for components; easier/more automated sync between CloverETL Designer and CloverETL Server."
Earn 20 points
Azure Data Factory is ranked 1st in Data Integration with 81 reviews while CloverETL is ranked 60th in Data Integration. Azure Data Factory is rated 8.0, while CloverETL is rated 7.0. The top reviewer of Azure Data Factory writes "The data factory agent is quite good but pricing needs to be more transparent". On the other hand, the top reviewer of CloverETL writes "Provides wealth of pre-defined, customizable components, and descriptive logging for errors". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and Microsoft Azure Synapse Analytics, whereas CloverETL is most compared with iWay Universal Adapter Framework and Talend Open Studio.
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