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 great technology."
"When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"Databricks' Lakehouse architecture has been most useful for us. The data governance has been absolutely efficient in between other kinds of solutions."
"Databricks allows me to automate the creation of a cluster, optimized for machine learning and construct AI machine learning models for the client."
"I haven't heard about any major stability issues. At this time I feel like it's stable."
"The most valuable feature of Databricks is the integration with Microsoft Azure."
"It can send out large data amounts."
"I like how easy it is to share your notebook with others. You can give people permission to read or edit. I think that's a great feature. You can also pull in code from GitHub pretty easily. I didn't use it that often, but I think that's a cool feature."
"This solution is easy to use and especially good at data preparation and wrapping."
"It has allowed us to easily implement advanced analytics into various processes."
"The product is open-source and therefore free to use."
"KNIME is quite scalable, which is one of the most important features that we found."
"The product is very easy to understand even for non-analytical stakeholders. Sometimes we provide them with KNIME workflows and teach them how to run it on their own machine."
"One of the greatest advantages of KNIME is that it can be used by those without any coding experience. those with no coding background can use it."
"All of the features related to the ETL are fantastic. That includes the connectors to other programs, databases, and the meta node function."
"There are a lot of connectors available in KNIME."
"The solution could be improved by integrating it with data packets. Right now, the load tables provide a function, like team collaboration. Still, it's unclear as to if there's a function to create different branches and/or more branches. Our team had used data packets before, however, I feel it's difficult to integrate the current with the previous data packets."
"We'd like a more visual dashboard for analysis It needs better UI."
"There could be more support for automated machine learning in the database. I would like to see more ways to do analysis so that the reporting is more understandable."
"It would be great if Databricks could integrate all the cloud platforms."
"In the future, I would like to see Data Lake support. That is something that I'm looking forward to."
"The query plan is not easy with Databrick's job level. If I want to tune any of the code, it is not easily available in the blogs as well."
"The product should incorporate more learning aspects. It needs to have a free trial version that the team can practice."
"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."
"The visualization functionalities are not good (cannot be compared to, for instance, the possibilities in R)."
"The documentation needs a proper rework. "
"From the point of view of the interface, they can do a little bit better."
"Compared to the other data tools on the market, the user interface can be improved."
"KNIME is not good at visualization."
"The license is quite expensive for us."
"There should be better documentation and the steps should be easier."
"The ability to handle large amounts of data and performance in processing need to be improved."
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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