We performed a comparison between Databricks and KNIME 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."In the manufacturing industry, Databricks can be beneficial to use because of machine learning. It is useful for tasks, such as product analysis or predictive maintenance."
"The time travel feature is the solution's most valuable aspect."
"The technical support is good."
"It can send out large data amounts."
"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."
"A very valuable feature is the data processing, and the solution is specifically good at using the Spark ecosystem."
"The setup was straightforward."
"Databricks has helped us have a good presence in data."
"What I like most about KNIME is that it's user-friendly. It's a low-code, no-code tool, so students don't need coding knowledge. You can make use of different kinds of nodes. KNIME even has a good description of each node."
"Key features include: very easy-to-use visual interface; Help functions and clear explanations of the functionalities and the used algorithms; Data Wrangling and data manipulation functionalities are certainly sufficient, as well as the looping possibilities which help you to automate parts of the analysis."
"We have found KNIME valuable when it comes to its visualization."
"I was able to apply basic algorithms through just dragging and dropping."
"Automation is most valuable. It allows me to automatically download information from different sources, and once I create a workflow, I can apply it anytime I want. So, there is efficiency at the same time."
"From a user-friendliness perspective, it's a great tool."
"The most valuable is the ability to seamlessly connect operators without the need for extensive programming."
"The product is open-source and therefore free to use."
"It would be very helpful if Databricks could integrate with platforms in addition to Azure."
"Databricks can improve by making the documentation better."
"It would be nice to have more guidance on integrations with ETLs and other data quality tools."
"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."
"There are no direct connectors — they are very limited."
"The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment."
"In the next release, I would like to see more optimization features."
"Databricks would have more collaborative features than it has. It should have some more customization for the jobs."
"The data visualization part is the area most in need of improvement."
"Not just for KNIME, but generally for software and analyzing data, I would welcome facilities for analyzing different sorts of scale data like Likert scales, Thurstone scales, magnitude ratio scales, and Guttman scales, which I don't use myself."
"It needs more examples, use cases, and MOOC to learn, especially with respect to the algorithms and how to practically create a flow from end-to-end."
"It's difficult to provide input on the improvement area because it's more of self-learning. However, there are times when I am not able to do certain things. I don't know if it's because the solution doesn't allow me or if it's because of the lack of knowledge."
"I've had some problems integrating KNIME with other solutions."
"KNIME is not good at visualization."
"The ability to handle large amounts of data and performance in processing need to be improved."
"If they had a more structured training model it would be very helpful."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while KNIME is ranked 4th in Data Science Platforms with 50 reviews. Databricks is rated 8.2, while KNIME 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 KNIME writes "A low-code platform that reduces data mining time by linking script". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Dremio and Microsoft Azure Machine Learning Studio, whereas KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Dataiku and Amazon SageMaker. See our Databricks vs. KNIME report.
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