We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"The most valuable features are data virtualization and reporting."
"Deployment was simple and straightforward."
"It is easy to use, and it is quick for developing things. It is fairly powerful, and it can integrate with a lot of different platforms without much hassle."
"Ease and speed of building integrations, especially integrations between different applications, such as our Hospital Information System."
"It has helped us monetize."
"Can manage a huge quantity of data and provide reliability."
"The number of docs has been reduced drastically, which is very good."
"It has a Data Catalog that uses the Model repository."
"Complex transformations can be easily achieved by using PowerCenter. The processing layer does transformations and other things. About 80% of my transformations can be achieved by using the middle layer. For the remaining 15% to 20% transformations, I can go in and create stored procedures in the respective databases. Mapplets is the feature through which we can reuse transformations across pipelines. Transformations and caching are the key features that we have been using frequently. Informatica PowerCenter is one of the best solutions or products in the data integration space. We have extensively used PowerCenter for integration purposes. We usually look at the best bridge solution in our architecture so that it can sustain for maybe a couple of years. Usually, we go with the solution that fits best and has proven and time-tested technology."
"The technical support could be a little better."
"The documentation could be improved."
"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."
"Requires an established data center because there is no option for software as a service."
"Its scalability can be improved. It is not scalable."
"The solution can improve by providing more connectivity by having native ODBC or JDBC connections available. It will be easier and more people could start using it."
"The only problem with this product is the level of complexity with the number of levels of transformation that you have to go through."
"The pricing could be improved."
"Integrating new tools can be tricky and challenging."
"I think that this product is too expensive for smaller companies."
"Licensing costs are excessive and pose an obstacle to someone who lacks familiarity with the solution and wishes to have a proper understanding of it."
"Our customers pay a licensing fee yearly."
"The pricing is a little expensive, but in the same range as IBM and other competitors."
"It's much more expensive, almost three times more expensive than most other solutions."
"Its maintenance is expensive."
"The price of this solution is high."
"It is for big enterprises. We have leveraged Informatica for big enterprises but not for small and medium enterprises because it is a very costly product as compared to other products. We propose this solution only for enterprise customers. For small to medium enterprises, we would propose the Microsoft solution. Its licensing is currently bundle-wise. It should be features-wise and not bundle-wise."
"Our client has purchased the license, and we are using it."
Earn 20 points
IBM Cloud Pak® for Data is a fully-integrated data and AI platform that modernizes how businesses collect, organize and analyze data to infuse AI throughout their organizations. Cloud-native by design, the platform unifies market-leading services spanning the entire analytics lifecycle. From data management, DataOps, governance, business analytics and automated AI, IBM Cloud Pak for Data helps eliminate the need for costly, and often competing, point solutions while providing the information architecture you need to implement AI successfully.
Building on the streamlined hybrid-cloud foundation of Red Hat® OpenShift®, IBM Cloud Pak for Data takes advantage of the underlying resource and infrastructure optimization and management. The solution fully supports multicloud environments such as Amazon Web Services (AWS), Azure, Google Cloud, IBM Cloud™ and private cloud deployments. Find out how IBM Cloud Pak for Data can lower your total cost of ownership and accelerate innovation.
Enterprise data integration platform to help organizations access, transform, and integrate data from a variety of systems.
IBM Cloud Pak for Data is ranked 40th in Data Integration Tools with 1 review while Informatica PowerCenter is ranked 1st in Data Integration Tools with 20 reviews. IBM Cloud Pak for Data is rated 5.0, while Informatica PowerCenter is rated 8.4. The top reviewer of IBM Cloud Pak for Data writes "Good reporting, but resource utilization is high and technical support can be improved". On the other hand, the top reviewer of Informatica PowerCenter writes "A stable, scalable, and mature solution for complex transformations and data integration". IBM Cloud Pak for Data is most compared with Azure Data Factory, Palantir Foundry, Denodo, Mule Anypoint Platform and SAS Data Management, whereas Informatica PowerCenter is most compared with Informatica Cloud Data Integration, SSIS, Azure Data Factory, Oracle Data Integrator (ODI) and Informatica PowerExchange.
See our list of best Data Integration Tools vendors.
We monitor all Data Integration Tools 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.