We performed a comparison between Databricks and QlikView based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."
"We can scale the product."
"The most valuable aspect of the solution is its notebook. It's quite convenient to use, both terms of the research and the development and also the final deployment, I can just declare the spark jobs by the load tables. It's quite convenient."
"The solution is an impressive tool for data migration and integration."
"This solution offers a lake house data concept that we have found exciting. We are able to have a large amount of data in a data lake and can manage all relational activities."
"The solution is very simple and stable."
"The most valuable feature is the ability to use SQL directly with Databricks."
"We like that this solution can handle a wide variety and velocity of data engineering, either in batch mode or real-time."
"If you correctly use the product for your use cases, it provides value for money."
"Associative model - no more cubes."
"You can do a lot of things on the back end which are not possible in the other solutions on the market."
"Once you open it up, you see everything that you can do."
"The most valuable feature of QlikView is the integration with other third-party tools."
"QlikView is one of the strongest tools, I would say. Also, it has a very vast capability to process the data"
"It enables us to configure various elements, such as dashboard settings, including factors like color schemes and other customization parameters."
"A well designed app brings freedom of inquiry to meetings, allowing me to answer questions in real time and this has transformed progress and outputs of our monthly group meeting."
"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."
"It should have more compatible and more advanced visualization and machine learning libraries."
"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."
"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."
"CI/CD needs additional leverage and support."
"The integration features could be more interesting, more involved."
"It would be better if it were faster. It can be slow, and it can be super fast for big data. But for small data, sometimes there is a sub-second response, which can be considered slow. In the next release, I would like to have automatic creation of APIs because they don't have it at the moment, and I spend a lot of time building them."
"Databricks' technical support takes a while to respond and could be improved."
"I really wish the application was easier to use in the development phase."
"Although Qliktech's road map clearly states that QlikView has a long way to go, most of the R&D effort seems to be benefiting Qlik Sense."
"There is a challenge on the frontend when it comes to browsing data through QlikView, as it isn't entirely compatible with other platforms we use."
"Needs improvement with UI transparency."
"Installation and deployment could be made easier and quicker."
"Scalability really depends on the size of your data and QlikView server architecture. For the biggest data sets, it could become an issue at some point."
"Sometimes, dealing with complex reports requires more effort, which could be really improved."
"Error handling."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while QlikView is ranked 5th in Reporting with 158 reviews. Databricks is rated 8.2, while QlikView is rated 8.2. 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 QlikView writes "Useful for data visualization and business intelligence". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Microsoft Azure Machine Learning Studio and Dremio, whereas QlikView is most compared with Tableau, Microsoft Power BI, Amazon QuickSight, SQL Server and TIBCO Spotfire.
We monitor all Data Science Platforms 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.
