We performed a comparison between CloverETL and Google Cloud Datalab based on real PeerSpot user reviews.
Find out what your peers are saying about Tableau, Qlik, Splunk and others in Data Visualization."Server features for scheduler: It is very easy to schedule jobs and monitor them. The interface is easy to use."
"Connectivity to various data sources: The ability to extract data from different data sources gives greater flexibility."
"No dependence on native language and ease of use."
"Key features include wealth of pre-defined components; all components are customizable; descriptive logging, especially for error messages."
"All of the features of this product are quite good."
"Google Cloud Datalab is very customizable."
"The infrastructure is highly reliable and efficient, contributing to a positive experience."
"The APIs are valuable."
"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."
"Needs: easier automated failure recovery; more, and more intuitive auto-generated/filled-in code for components; easier/more automated sync between CloverETL Designer and CloverETL Server."
"Its documentation could be improved."
"Resource management: We typically run out of heap space, and even the allocation of high heap space does not seem to be enough."
"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 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."
Earn 20 points
CloverETL is ranked 41st in Data Visualization while Google Cloud Datalab is ranked 20th in Data Visualization with 5 reviews. CloverETL is rated 7.0, while Google Cloud Datalab is rated 7.6. The top reviewer of CloverETL writes "Provides wealth of pre-defined, customizable components, and descriptive logging for errors". On the other hand, the top reviewer of Google Cloud Datalab writes "Easy to setup, stable and easy to design data pipelines". CloverETL is most compared with iWay Universal Adapter Framework and Talend Open Studio, whereas Google Cloud Datalab is most compared with Databricks, IBM SPSS Statistics, Cloudera Data Science Workbench, IBM SPSS Modeler and KNIME.
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We monitor all Data Visualization 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.
