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."Databricks' most valuable feature is the data transformation through PySpark."
"The simplicity of development is the most valuable feature."
"There are good features for turning off clusters."
"The most valuable feature of Databricks is the integration with Microsoft Azure."
"Ability to work collaboratively without having to worry about the infrastructure."
"The most valuable feature is the ability to use SQL directly with Databricks."
"Databricks allows me to automate the creation of a cluster, optimized for machine learning and construct AI machine learning models for the client."
"The initial setup is pretty easy."
"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."
"Reporting is a valuable feature of the solution."
"The most valuable feature of Qlik Analytics Platform is its Change Data Capture capability."
"It is a great platform for third party extensions, has an open API, and there are no black boxes."
"The interface of Databricks could be easier to use when compared to other solutions. It is not easy for non-data scientists. The user interface is important before we had to write code manually and as solutions move to "No code AI" it is critical that the interface is very good."
"Databricks' technical support takes a while to respond and could be improved."
"The data visualization for this solution could be improved. They have started to roll out a data visualization tool inside Databricks but it is in the early stages. It's not comparable to a solution like Power BI, Luca, or Tableau."
"The product should incorporate more learning aspects. It needs to have a free trial version that the team can practice."
"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."
"I would love an integration in my desktop IDE. For now, I have to code on their webpage."
"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."
"Implementation of Databricks is still very code heavy."
"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."
"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])."
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 Data Science Studio, 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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