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."Databricks' Lakehouse architecture has been most useful for us. The data governance has been absolutely efficient in between other kinds of solutions."
"We like that this solution can handle a wide variety and velocity of data engineering, either in batch mode or real-time."
"I like how easy it is to share your notebook with others. You can give people permission to read or edit. I think that's a great feature. You can also pull in code from GitHub pretty easily. I didn't use it that often, but I think that's a cool feature."
"We are completely satisfied with the ease of connecting to different sources of data or pocket files in the search"
"When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"The initial setup phase of Databricks was good."
"The solution is very simple and stable."
"Databricks gives us the ability to build a lakehouse framework and do everything implicit to this type of database structure. We also like the ability to stream events. Databricks covers a broad spectrum, from reporting and machine learning to streaming events. It's important for us to have all these features in one platform."
"The infrastructure is highly reliable and efficient, contributing to a positive experience."
"Google Cloud Datalab is very customizable."
"The APIs are valuable."
"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."
"I would like more integration with SQL for using data in different workspaces."
"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."
"If I want to create a Databricks account, I need to have a prior cloud account such as an AWS account or an Azure account. Only then can I create a Databricks account on the cloud. However, if they can make it so that I can still try Databricks even if I don't have a cloud account on AWS and Azure, it would be great. That is, it would be nice if it were possible to create a pseudo account and be provided with a free trial. It is very essential to creating a workforce on Databricks. For example, students or corporate staff can then explore and learn Databricks."
"A lot of people are required to manage this solution."
"It would be great if Databricks could integrate all the cloud platforms."
"Pricing is one of the things that could be improved."
"There is room for improvement in visualization."
"There should be better integration with other platforms."
"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 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."
"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."
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, 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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