We performed a comparison between Google Cloud Datalab and Informatica PowerCenter based on real PeerSpot user reviews.
Find out in this report how the two Data Visualization solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."
"Google Cloud Datalab is very customizable."
"The infrastructure is highly reliable and efficient, contributing to a positive experience."
"The APIs are valuable."
"All of the features of this product are quite good."
"The most valuable features are the monitoring tools and the reporting manager."
"In the end, you have structured, proper data for use in an integrated BI solution."
"The most complex task, in this case, was to read and transform BLOB data, and Java transformation in Informatica Power Center was a great solution."
"Technical support, and their approach is good. They have a support portal and support tickets. If you open a ticket it has multiple levels of severity from level one to very high or critical."
"The most valuable feature is the new Data Lake feature, which provides the basic capabilities needed."
"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."
"It has helped us monetize."
"Ease and speed of building integrations, especially integrations between different applications, such as our Hospital Information System."
"The product must be made more user-friendly."
"The interface should be more user-friendly."
"There is room for improvement in the graphical user interface. So that the initial user would use it properly, that would be a good option."
"We have also encountered challenges during our transition period in terms of data control and segmentation. The management of each channel and data structure as it has its own unique characteristics requires very detailed and precise control. The allocation should be appropriate and the complexity increases due to the different time zones and geographic locations of our clients. The process usually involves migrating the existing database sets to gcp and ensure data integrity is maintained. This is the only challenge that we faced while navigating the integers of the solution and honestly it was an interesting and unique experience."
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
"Lacks ability to calculate cost of the product."
"In terms of performance improvement and tuning, there should be a bit more guidance and documentation."
"It should be more cloud-centric than on-prem-centric."
"The real-time database connectivity when getting the real-time data using the VPN is an area that needs improvement."
"The UI is a little outdated."
"What I didn't like about it is that the platform itself is not great at distributed processing. When you need high parallel processing, it has some inherent issues. We had to use Java transformation, and it did not go very well. I have heard that it is going to the cloud, but we haven't tried that."
"The price of the product is an area of concern where improvements are required, considering the fact that the present licensing charges of the tool are expensive."
"An issue which should be addressed is that the solution only allows us to do structured, as opposed to unstructured, data processing."
Google Cloud Datalab is ranked 20th in Data Visualization with 5 reviews while Informatica PowerCenter is ranked 5th in Data Visualization with 78 reviews. Google Cloud Datalab is rated 7.6, while Informatica PowerCenter is rated 8.0. The top reviewer of Google Cloud Datalab writes "Easy to setup, stable and easy to design data pipelines". 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". Google Cloud Datalab is most compared with Databricks, IBM SPSS Statistics, Cloudera Data Science Workbench, KNIME and Qlik Sense, whereas Informatica PowerCenter is most compared with Informatica Cloud Data Integration, Azure Data Factory, SSIS, Databricks and AWS Glue. See our Google Cloud Datalab vs. Informatica PowerCenter report.
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