We performed a comparison between Databricks and Google Cloud Datalab based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The initial setup phase of Databricks was good."
"Can cut across the entire ecosystem of open source technology to give an extra level of getting the transformatory process of the data."
"Databricks' Lakehouse architecture has been most useful for us. The data governance has been absolutely efficient in between other kinds of solutions."
"The most valuable feature of Databricks is the notebook, data factory, and ease of use."
"The solution is built from Spark and has integration with MLflow, which is important for our use case."
"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."
"The most valuable feature of Databricks is the integration of the data warehouse and data lake, and the development of the lake house. Additionally, it integrates well with Spark for processing data in production."
"The setup was straightforward."
"Google Cloud Datalab is very customizable."
"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."
"The infrastructure is highly reliable and efficient, contributing to a positive experience."
"The APIs are valuable."
"It's not easy to use, and they need a better UI."
"It would be great if Databricks could integrate all the cloud platforms."
"It would be nice to have more guidance on integrations with ETLs and other data quality tools."
"I have had some issues with some of the Spark clusters running on Databricks, where the Spark runtime and clusters go up and down, which is an area for improvement."
"This solution only supports queries in SQL and Python, which is a bit limiting."
"I have seen better user interfaces, so that is something that can be improved."
"The integration features could be more interesting, more involved."
"Databricks would benefit from enhanced metrics and tighter integration with Azure's diagnostics."
"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."
"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."
"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."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while Google Cloud Datalab is ranked 15th in Data Science Platforms with 5 reviews. Databricks is rated 8.2, while Google Cloud Datalab is rated 7.6. The top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". On the other hand, the top reviewer of Google Cloud Datalab writes "Easy to setup, stable and easy to design data pipelines". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku Data Science Studio, Microsoft Azure Machine Learning Studio and Dremio, whereas Google Cloud Datalab is most compared with IBM SPSS Statistics, Cloudera Data Science Workbench, KNIME, Qlik Sense and Microsoft Azure Machine Learning Studio. See our Databricks vs. Google Cloud Datalab report.
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