We performed a comparison between Databricks and Qlik Sense 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 solution is very simple and stable."
"The solution offers a free community version."
"The solution is built from Spark and has integration with MLflow, which is important for our use case."
"The simplicity of development is the most valuable feature."
"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 integration with Python and the notebooks really helps."
"We have the ability to scale, collaborate and do machine learning."
"The main features of the solution are efficiency."
"From siloed reports, we went to a centralized knowledge hub, combining cross-functional data, and helping decision-makers see the data as a whole, therefore making more informed decisions."
"Qlik Sense brings in the concept of shared libraries where one user can create custom dimensions (even with drill-down functionality), measures, and even visualizations and save it to the "Master Items," from which the other users can simply drag and drop to use it for their analysis."
"The most valuable feature is flexibility."
"The most valuable feature is the interface for the end-user."
"The product has many great features like easy and fast implementation, flexible data loading, and in-memory processing, but the Set Analysis is what I think is the most valuable. It makes the product very powerful."
"It is very easy to use, and the Qlik data engine has been able to handle everything we have thrown at it."
"The reports are better looking than in QlikView."
"We can generate various graphs, various reports and we can mainly use it for dashboard related things. We can create a dashboard with live data and we can make decisions based on this information,"
"The solution could be improved by adding a feature that would make it more user-friendly for our team. The feature is simple, but it would be useful. Currently, our team is more familiar with the language R, but Databricks requires the use of Jupyter Notebooks which primarily supports Python. We have tried using RStudio, but it is not a fully integrated solution. To fully utilize Databricks, we have to use the Jupyter interface. One feature that would make it easier for our team to adopt the Jupyter interface would be the ability to select a specific variable or line of code and execute it within a cell. This feature is available in other Jupyter Notebooks outside of Databricks and in our own IDE, but it is not currently available within Databricks. If this feature were added, it would make the transition to using Databricks much smoother for our team."
"Scalability is an area with certain shortcomings. The solution's scalability needs improvement."
"The product should incorporate more learning aspects. It needs to have a free trial version that the team can practice."
"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 of data could be a bit better."
"Databricks is not geared towards the end-user, but rather it is for data engineers or data scientists."
"The stability of the clusters or the instances of Databricks would be better if it was a much more stable environment. We've had issues with crashes."
"There is room for improvement in visualization."
"There is room for improvement in the storytelling mode and the report sharing. Qlik Sense also does not have a subscription base like Power BI. So a lot of the analysis is housed in community pages that are managed by either the author or a database administrator, or whoever the Qlik Sense manager is there."
"In my opinion, collaborative development of the Qlik Apps is a bit tricky and difficult in the Qlik Sense Cloud."
"There is an inability to effectively manage (pre)caching (scheduling, assigning for respective user groups, etc), especially without community extensions or uour own development."
"Ad-hoc reporting capabilities would be ideal."
"Advanced graphs or visualizations must be in the built-in product, instead of building with open API extensions or mashups."
"More focus needs to be on data streaming/real-time data reporting."
"Qlik has a fast learning curve due to great online training resources (Qlik continuous classroom), but those are lacking the advance features like building extensions and using the API."
"There is room for improvement in the learning curve when getting started, but training resources have been growing."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while Qlik Sense is ranked 2nd in Data Visualization with 114 reviews. Databricks is rated 8.2, while Qlik Sense is rated 8.6. 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 Qlik Sense writes "Customizable with good ROI and a quick learning curve". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Dremio and Microsoft Azure Machine Learning Studio, whereas Qlik Sense is most compared with Tableau, Amazon QuickSight, Microsoft Power BI, Apache Superset and TIBCO Spotfire. See our Databricks vs. Qlik Sense report.
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