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."The infrastructure is highly reliable and efficient, contributing to a positive experience."
"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."
"All of the features of this product are quite good."
"Google Cloud Datalab is very customizable."
"The APIs are valuable."
"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."
"It's very easy to use it to develop mappings and workflows."
"The number of docs has been reduced drastically, which is very good."
"The most valuable features are the monitoring tools and the reporting manager."
"It is UI friendly and has all the advantages of an ETL tool."
"It has good standard features for ETL development."
"If the systems get migrated or upgraded, the amount of resources required are very minimal. We can change the connections and establish a new connection. It's very helpful."
"I like the automated scheduling feature."
"The product must be made more user-friendly."
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
"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."
"The pricing could be improved."
"Include more instruments for LOGs analysis, interpretation, and job corrections."
"Now they are migrating to a new version, and they have something that is called Informatica Developer. Previously, they just had PowerCenter. Now, when they move everything to Informatica Developer it's not as good or stable like it was when it was PowerCenter, though it has some nice features. This Developer tool could be better."
"We had to take on a large volume of data from the legacy Sybase system. This was taking a very long time, i.e., more than a day. We were trying to improve it with partitions to gpload, but we were told that we can't go more than four partitions."
"We need another tool for monitoring. It would be easier if all the features were consolidated into one tool."
"While Informatica is great for data-integration, it does not have any analytics features. Thus, organizations have to always look for another product for their BI needs."
"The licensing cost for Informatica is very high. Other all-in-one solutions have much lower prices than Informatica."
"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."
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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