We performed a comparison between Databricks and ELK Kibana 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."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."
"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."
"Databricks has a scalable Spark cluster creation process. The creators of Databricks are also the creators of Spark, and they are the industry leaders in terms of performance."
"Easy to use and requires minimal coding and customizations."
"The most valuable feature is the Spark cluster which is very fast for heavy loads, big data processing and Pi Spark."
"Databricks provides a consistent interface for data engineers to work with data in a consistent language on a single integrated platform for ingesting, processing, and serving data to the end user."
"The solution is easy to use and has a quick start-up time due to being on the cloud."
"The load distribution capabilities are good, and you can perform data processing tasks very quickly."
"The optimization and flexibility of visualization tools."
"Having a tool where you can find logs that were generated months ago, and being able to search over a long period of time, is great."
"The automatic update of the graphs from a dashboard is very convenient."
"CI/CD needs additional leverage and support."
"There could be more support for automated machine learning in the database. I would like to see more ways to do analysis so that the reporting is more understandable."
"The solution could be improved by integrating it with data packets. Right now, the load tables provide a function, like team collaboration. Still, it's unclear as to if there's a function to create different branches and/or more branches. Our team had used data packets before, however, I feel it's difficult to integrate the current with the previous data packets."
"The integration features could be more interesting, more involved."
"Can be improved by including drag-and-drop features."
"I would love an integration in my desktop IDE. For now, I have to code on their webpage."
"We'd like a more visual dashboard for analysis It needs better UI."
"Databricks' technical support takes a while to respond and could be improved."
"Having a kind of wizard that would help you when you are typing your search would make it easier and quicker to refine your search, and ultimately find what you are looking for."
"This solution should allow the user to combine two indices into one graph."
"Security could be improved thereby avoiding the necessity of a third party plugin."
Earn 20 points
Databricks is ranked 1st in Data Science Platforms with 77 reviews while ELK Kibana doesn't meet the minimum requirements to be ranked in Data Science Platforms. Databricks is rated 8.2, while ELK Kibana is rated 7.2. 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 ELK Kibana writes "Visualization tools are optimized providing us with increased flexibility". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio and Azure Stream Analytics, whereas ELK Kibana is most compared with Splunk Enterprise Security. See our Databricks vs. ELK Kibana report.
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