We performed a comparison between Dataiku Data Science Studio and KNIME based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."Cloud-based process run helps in not keeping the systems on while processes are running."
"Data Science Studio's data science model is very useful."
"The most valuable feature of this solution is that it is one tool that can do everything, and you have the ability to very easily push your design to prediction."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"The most valuable feature is the set of visual data preparation tools."
"The solution is quite stable."
"Extremely easy to use with its GUI-based functionality and large compatibility with various data sources. Also, maintenance processes are much more automated than ever, with fewer errors."
"We have found KNIME valuable when it comes to its visualization."
"All of the features related to the ETL are fantastic. That includes the connectors to other programs, databases, and the meta node function."
"The most useful features are the readily available extensions that speed up the work."
"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."
"Stability is excellent. I would give it a nine out of ten."
"It's a huge tool with machine learning features as well."
"Valuable features include visual workflow creation, workflow variables (parameterisation), automatic caching of all intermediate data sets in the workflow, scheduling with the server."
"The ability to have charts right from the explorer would be an improvement."
"The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective."
"In the next release of this solution, I would like to see deep learning better integrated into the tool and not simply an extension or plugin."
"There were stability issues: 1) SQL operations, such as partitioning, had bugs and showed wrong results. 2) Due to server downtime, scheduled processes used to fail. 3) Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"I think it would help if Data Science Studio added some more features and improved the data model."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"It's pretty straightforward to understand. So, if you understand what the pipeline is, you can use the drag-and-drop functionality without much training. Doing the same thing in Python requires so much more training. That's why I use KNIME."
"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."
"In my environment, I need to access a lot of servers with different characteristics and access methods. Some of my servers have to be accessed using proxy which is not supported by KNIME, so I still need to create the middleware to supply the source of my KNIME configurations."
"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."
"There are some parameters that I would like to have at a bigger scale. The upper limit of one node that tries to find spots or areas in photos was too small for us. It would need to be bigger."
"They should look at other vendors like Alteryx that are more user friendly and modern."
"There should be better documentation and the steps should be easier."
"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."
Dataiku Data Science Studio is ranked 6th in Data Science Platforms while KNIME is ranked 4th in Data Science Platforms with 50 reviews. Dataiku Data Science Studio is rated 8.2, while KNIME is rated 8.2. The top reviewer of Dataiku Data Science Studio writes "The model is very useful". On the other hand, the top reviewer of KNIME writes "A low-code platform that reduces data mining time by linking script". Dataiku Data Science Studio is most compared with Databricks, Alteryx, Microsoft Azure Machine Learning Studio, RapidMiner and Amazon SageMaker, whereas KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Weka and IBM SPSS Modeler.
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