We performed a comparison between Azure Data Factory and Informatica Data Integration Hub based on real PeerSpot user reviews.
Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
"Its integrability with the rest of the activities on Azure is most valuable."
"It is easy to deploy workflows and schedule jobs."
"Powerful but easy-to-use and intuitive."
"We haven't had any issues connecting it to other products."
"What I like best about Azure Data Factory is that it allows you to create pipelines, specifically ETL pipelines. I also like that Azure Data Factory has connectors and solves most of my company's problems."
"It is beneficial that the solution is written with Spark as the back end."
"UI is easy to navigate and I can retrieve VTL code without knowing in-depth coding languages."
"I like its integration with SQL pools, its ability to work with Databricks, its pipelines, and the serverless architecture are the most effective features."
"The MDM solution is capable of integrating multiple systems, so it helped us to solve the purpose of centralizing the depository as well as the standardization of mass data. It takes away all the ambiguity around data integrity issues or all the process challenges which happen when every stage of a process uses a different source as master data."
"Performance and flexibility-wise, they're very user-friendly."
"The technical support services are good."
"There is no built-in pipeline exit activity when encountering an error."
"There should be a way that it can do switches, so if at any point in time I want to do some hybrid mode of making any data collections or ingestions, I can just click on a button."
"Data Factory could be improved in terms of data transformations by adding more metadata extractions."
"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."
"It would be better if it had machine learning capabilities."
"There is room for improvement primarily in its streaming capabilities. For structured streaming and machine learning model implementation within an ETL process, it lags behind tools like Informatica."
"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."
"We are too early into the entire cycle for us to really comment on what problems we face. We're mostly using it for transformations, like ETL tasks. I think we are comfortable with the facts or the facts setting. But for other parts, it is too early to comment on."
"They could provide more robust performance for data integration processes. It would help in improving the data quality more efficiently."
"When it comes to UI look and feel and user experience, Informatica is not as good as other solutions."
"The initial setup was not very straightforward. Not complex, but not very simple either."
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Azure Data Factory is ranked 1st in Data Integration with 81 reviews while Informatica Data Integration Hub is ranked 37th in Data Integration with 3 reviews. Azure Data Factory is rated 8.0, while Informatica Data Integration Hub is rated 8.0. 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 Informatica Data Integration Hub writes "Excellent at standardizing mass data and capable of integrating with multiple solutions ". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and IBM InfoSphere DataStage, whereas Informatica Data Integration Hub is most compared with Informatica PowerCenter, AWS Database Migration Service, SAP Data Hub, Mule Anypoint Platform and SAS Data Management. See our Azure Data Factory vs. Informatica Data Integration Hub report.
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