We performed a comparison between Azure Data Factory and Informatica Powercenter based on our users’ reviews in four categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: Based on the parameters we compared, Azure Data Factory and Informatica Powercenter are very comparable to one another. Overall, PeerSpot users found that both solutions have helpful features. However, users found Informatica Powercenter to be more expensive than Azure Data Factory.
"The overall performance is quite good."
"The solution is okay."
"The most important feature is that it can help you do the multi-threading concepts."
"It makes it easy to collect data from different sources."
"I enjoy the ease of use for the backend JSON generator, the deployment solution, and the template management."
"The most valuable feature is the copy activity."
"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."
"Azure Data Factory became more user-friendly when data-flows were introduced."
"I like the automated scheduling feature."
"Once you have learned Informatica, it is very easy to use."
"Can manage a huge quantity of data and provide reliability."
"The setup is very simple."
"The most valuable feature of Informatica PowerCenter is data transformation and user-friendliness."
"Informatica PowerCenter has good user feedback. The developers can easily make mappings in the solution."
"The greatest feature is that it is very easy to have someone come in and jump right in. It is one of the nicest tools in terms of getting a person acquainted quickly."
"The interface is very clean and clear."
"We require Azure Data Factory to be able to connect to Google Analytics."
"One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases."
"My only problem is the seamless connectivity with various other databases, for example, SAP."
"If the user interface was more user friendly and there was better error feedback, it would be helpful."
"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."
"DataStage is easier to learn than Data Factory because it's more visual. Data Factory has some drag-and-drop options, but it's not as intuitive as DataStage. It would be better if they added more drag-and-drop features. You can start using DataStage without knowing the code. You don't need to learn how the code works before using the solution."
"Azure Data Factory uses many resources and has issues with parallel workflows."
"Azure Data Factory should be cheaper to move data to a data center abroad for calamities in case of disasters."
"Its interface can be modernized. It is an old product. I have been working with it for 14 years, and it still looks the same. It hasn't been modernized much. It also needs to handle more modern formats, such as JSON files. It works with the old text files and databases, but it does not always work with the newer, modern stuff. You need to make your own programs to support that kind of stuff. Support is also a kind of difficult with Informatica. They don't do direct support and rely on using their distributors around the globe for support, which means that you kind of have to go through this layer of different companies before you get help."
"It would be better if I could do all the work within a single window. If I'm working on any mapping and if I have to switch to sessions, I have to open a new window altogether. If I have to get into workflows, I have to open a new window. It was also very expensive. In the next release, I would like it to be more user-friendly."
"Its licensing can be improved. It should be features-wise and not bundle-wise. A bundle will definitely be costly. In addition, we might use one or two features. That's why the pricing model should be based on the features. The model should be flexible enough based on the features. Their support should also be more responsive to premium customers."
"An issue which should be addressed is that the solution only allows us to do structured, as opposed to unstructured, data processing."
"It would be good to recreate the entire interface to make it easier for users to build workflows."
"Informatica PowerCenter could improve by having a single interface because half of the system is still in the legacy interface and many other elements are moved to the developer client. It would be good if there was a single interface for the end user and developers."
"This product is going to decommission in the next couple of years."
"If you want to transfer a ZIP file, it is a pain. You need to use Command-Line. Sometimes we just want to transfer a file. It should be easy to move them from A to B."
Azure Data Factory is ranked 1st in Data Integration with 40 reviews while Informatica PowerCenter is ranked 3rd in Data Integration with 30 reviews. Azure Data Factory is rated 8.0, while Informatica PowerCenter is rated 8.0. The top reviewer of Azure Data Factory writes "The good, the bad and the lots of ugly". On the other hand, the top reviewer of Informatica PowerCenter writes "Stable, provides good support, and integrating it with other systems is very fast, but its pricing is expensive". Azure Data Factory is most compared with Alteryx Designer, Informatica Cloud Data Integration, Snowflake, Microsoft Azure Synapse Analytics and IBM InfoSphere DataStage, whereas Informatica PowerCenter is most compared with Informatica Cloud Data Integration, SSIS, Databricks, AWS Glue and Informatica PowerExchange. See our Azure Data Factory vs. Informatica PowerCenter report.
See our list of best Data Integration vendors.
We monitor all Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.