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."It's very simple to use Databricks Apache Spark."
"The solution is easy to use and has a quick start-up time due to being on the cloud."
"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 fast data loading process and data storage capabilities are great."
"Databricks' most valuable features are the workspace and notebooks. Its integration, interface, and documentation are also good."
"The ability to stream data and the windowing feature are valuable."
"Databricks has improved my organization by allowing us to transform data from sources to a different format and feed that to the analytics, business intelligence, and reporting teams. This tool makes it easy to do those kinds of things."
"The solution offers a free community version."
"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."
"This open-source product can compete with category leaders in ELT software."
"Stability is excellent. I would give it a nine out of ten."
"I would rate the stability of KNIME a ten out of ten."
"KNIME is easy to learn."
"The ETL which helps me to collect, reformat, and load the data from multiple sources into one destination, a storage database."
"Easy to connect with every database: We use queries from SQL, Redshift, Oracle."
"The most useful features are the readily available extensions that speed up the work."
"Generative AI is catching up in areas like data governance and enterprise flavor. Hence, these are places where Databricks has to be faster."
"Databricks doesn't offer the use of Python scripts by itself and is not connected to GitHub repositories or anything similar. This is something that is missing. if they could integrate with Git tools it would be an advantage."
"The integration features could be more interesting, more involved."
"In the next release, I would like to see more optimization features."
"The connectivity with various BI tools could be improved, specifically the performance and real time integration."
"Costs can quickly add up if you don't plan for it."
"The initial setup is difficult."
"There would also be benefits if more options were available for workers, or the clusters of the two points."
"The pricing needs improvement."
"Compared to the other data tools on the market, the user interface can be improved."
"The overall user experience feels unpolished. In particular: Data field type conversion is a real hassle, and date fields are a hassle; documentation is pretty poor; user community is average at best."
"The ability to handle large amounts of data and performance in processing need to be improved."
"I would like it to have data visualitation capabilities. Today I'm still creating my own data visualtions tools to present my reports."
"Though I can use KNIME in a 64-bit platform in the lab, it's missing some features. For example, from my laptop, I can use the image reader feature of KNIME. However, in the lab, the image reader node is missing."
"It could be easier to use."
"KNIME's licensing and data management aren't as straightforward relative to Alteryx. Alteryx's tools are more sophisticated, so you need fewer to use it compared to KNIME. I think tab implementation could be easier, too."
Databricks is ranked 1st in Data Science Platforms with 77 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, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio and Azure Stream Analytics, whereas KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Weka and SAS Analytics. See our Databricks vs. KNIME report.
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