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 solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."
"I like that it's a monolithic data platform. This is why we propose these solutions."
"The most valuable features of Azure Data Factory are the flexibility, ability to move data at scale, and the integrations with different Azure components."
"I can do everything I want with SSIS and Azure Data Factory."
"It's extremely consistent."
"Allows more data between on-premises and cloud solutions"
"The most valuable feature of this solution would be ease of use."
"It is a complete ETL Solution."
"We have found the PowerCenter and B2B data transformation most valuable."
"It's a complete package, which is why we use this solution."
"To me, what's most valuable in Informatica PowerCenter is the flexibility in building the integration pipeline. Usually, you need to have a platform to be able to integrate with different technologies, including legacy data such as the mainframe. The platform should also be rich enough to transform the data per your business requirement, with no restrictions. Rich integration and rich transformation capabilities are the two key capabilities in Informatica PowerCenter. The solution also offers ease of use. Another valuable feature of Informatica PowerCenter is the drag-and-drop integration because it's GUI-based, similar to IBM and Oracle."
"Informatica PowerCenter is very good for integrating a huge amount of data in a very short duration, such as a minute. It is also very easy to use. After you provide the source and the target, mappings are automatically done, which makes it easy to use for the development team."
"It has helped us monetize."
"The technical support is excellent."
"The most valuable feature is the new Data Lake feature, which provides the basic capabilities needed."
"The most valuable features are the monitoring tools and the reporting manager."
"Real-time replication is required, and this is not a simple task."
"Integration of data lineage would be a nice feature in terms of DevOps integration. It would make implementation for a company much easier. I'm not sure if that's already available or not. However, that would be a great feature to add if it isn't already there."
"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."
"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."
"Lacks in-built streaming data processing."
"Data Factory could be improved by eliminating the need for a physical data area. We have to extract data using Data Factory, then create a staging database for it with Azure SQL, which is very, very expensive. Another improvement would be lowering the licensing cost."
"Azure Data Factory's pricing in terms of utilization could be improved."
"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."
"If we could have the option of performance improvement within Informatica, and if it could have more features, that would be ideal."
"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."
"The solution could have better documentation on basic steps or blocks that specify what to do."
"PowerCenter could integrate better with cloud applications. We had to do a lot of configuration work using API integrations to connect with cloud applications. Informatica Cloud Data Integration has a generic connector that you can use directly, so it's much easier."
"It should be more cloud-centric than on-prem-centric."
"The multiple interfaces in Informatica PowerCenter are not great for the user experience. Because of this, I think it can cause confusion for any beginner developer."
"Unstructured data handling is an important area with a shortcoming that needs improvement in the solution."
"The documentation could be improved."
Azure Data Factory is ranked 1st in Data Integration with 81 reviews while Informatica PowerCenter is ranked 3rd in Data Integration with 78 reviews. Azure Data Factory is rated 8.0, while Informatica PowerCenter 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 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 Informatica Cloud Data Integration, Alteryx Designer, Snowflake, IBM InfoSphere DataStage and Palantir Foundry, whereas Informatica PowerCenter is most compared with Informatica Cloud Data Integration, SSIS, Databricks, AWS Glue and Oracle Data Integrator (ODI). See our Azure Data Factory vs. Informatica PowerCenter report.
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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.
