We performed a comparison between Databricks and Qlik Analytics Platform 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."Its lightweight and fast processing are valuable."
"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."
"One of the features provides nice interactive clusters, or compute instances that you don't really need to manage often."
"Can cut across the entire ecosystem of open source technology to give an extra level of getting the transformatory process of the data."
"There are good features for turning off clusters."
"The most valuable feature is the ability to use SQL directly with Databricks."
"Specifically for data science and data analytics purposes, it can handle large amounts of data in less time. I can compare it with Teradata. If a job takes five hours with Teradata databases, Databricks can complete it in around three to three and a half hours."
"Reporting is a valuable feature of the solution."
"It is a great platform for third party extensions, has an open API, and there are no black boxes."
"Qlik offers you all the features needed to extract the raw data from the source systems including an ETL layer to transform the data and to connect the multiple data sources into one data model, easy data sharing, security and scaling features, dashboards, and report functionality to share your data with your end-users."
"The most valuable feature of Qlik Analytics Platform is its Change Data Capture capability."
"There is room for improvement in the documentation of processes and how it works."
"The integration of data could be a bit better."
"I would love an integration in my desktop IDE. For now, I have to code on their webpage."
"I would like it if Databricks made it easier to set up a project."
"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."
"Databricks may not be as easy to use as other tools, but if you simplify a tool too much, it won't have the flexibility to go in-depth. Databricks is completely in the programmer's hands. I prefer flexibility rather than simplicity."
"It's not easy to use, and they need a better UI."
"Doesn't provide a lot of credits or trial options."
"It would be great if decentralized teams would have more features to manage the metadata on the dashboards, setup the specific user access rights and rules to govern incoming and outgoing data sets from/to other teams, and more features to separate the different data process layers (e.g. extraction, transformation [data quality, business rules])."
"More freedom for custom visuals and dashboard creation would be an improvement."
"One area where Qlik Analytics Platform could be improved is in providing better support for batch processing and traditional ETL workflows."
"The user experience needs to be improved."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while Qlik Analytics Platform is ranked 25th in Data Visualization with 4 reviews. Databricks is rated 8.2, while Qlik Analytics Platform is rated 8.4. 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 Analytics Platform writes "An easy-to-deploy solution with a variety of use cases and excellent reporting features". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Microsoft Azure Machine Learning Studio and Dremio, whereas Qlik Analytics Platform is most compared with Apache Superset and Qlik Sense. See our Databricks vs. Qlik Analytics Platform report.
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