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."When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"Databricks covers end-to-end data analytics workflow in one platform, this is the best feature of the solution."
"Ability to work collaboratively without having to worry about the infrastructure."
"Databricks integrates well with other solutions."
"I like that Databricks is a unified platform that lets you do streaming and batch processing in the same place. You can do analytics, too. They have added something called Databricks SQL Analytics, allowing users to connect to the data lake to perform analytics. Databricks also will enable you to share your data securely. It integrates with your reporting system as well."
"Databricks' most valuable feature is the data transformation through PySpark."
"The solution is very simple and stable."
"Automation with Databricks is very easy when using the API."
"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."
"Overall KNIME serves its purpose and does a good job."
"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."
"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."
"It also has very good fundamental machine learning. It has decision trees, linear regression, and neural nets. It has a lot of text mining facilities as well. It's fairly fully-featured."
"Usability, and organising workflows in very neat manner. Controlling workflow through variables is something amazing."
"KNIME is easy to learn."
"It's a very powerful and simple tool to use."
"Overall it's a good product, however, it doesn't do well against any individual best-of-breed products."
"I have seen better user interfaces, so that is something that can be improved."
"Doesn't provide a lot of credits or trial options."
"I would like to see the integration between Databricks and MLflow improved. It is quite hard to train multiple models in parallel in the distributed fashions. You hit rate limits on the clients very fast."
"When I used the support, I had communication problems because of the language barrier with the agent. The accent was difficult to understand."
"Databricks could improve in some of its functionality."
"There is room for improvement in visualization."
"The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment."
"When deploying models on a regular system, it works fine. However, when accuracy is a priority, hyperparameter tuning is necessary. Currently, KNIME doesn't have the best tools for this which they could improve in this area."
"I'd like something that would make it easier to connect/parse websites, although I will fully admit that I'm not as proficient in KNIME as I would like to be, so it could be I'm just missing something."
"KNIME could improve when it comes to large data markets."
"KNIME can improve by adding more automation tools in the query, similar to UiPath or Blue Prism. It would make the data collection and cleanup duties more versatile."
"Both RapidMiner and KNIME should be made easier to use in the field of deep learning."
"One thing to consider is that the prebuilt nodes may not always be a perfect fit for your specific needs, although most of the time, they work quite well."
"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."
"I would like to see better web scraping because every time I tried, it was not up to par, although you can use Python script."
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 Data Science Studio, Microsoft Azure Machine Learning Studio and Dremio, 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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