We performed a comparison between Alteryx and KNIME based on our users’ reviews in four categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: Although KNIME’s open-source version is flexible and cost-effective and their service is top-notch, Alteryx offers an extremely intuitive intelligence suite and overall the solution is very robust and modern and the GUI is very user friendly. Ultimately, Alteryx finishes ahead of KNIME on most occasions.
"The philosophy of the citizen data scientist is the key piece, which means the no-code analytics capability. This is the feature that attracted us the most."
"Alteryx helps me do a lot of automation. The best thing about Alteryx is that you don't have to repeat the workflow over and over again. Unlike Excel, where you need to write formulas for each new file, Alteryx follows a consistent process. You can schedule and automate the workflow, even if the files change."
"Technical support is very helpful."
"Alteryx speeds up the time to obtain business answers/insights on data."
"The solution offers excellent predicting power. The accuracy and confidence have been great."
"The most valuable feature of Alteryx is its performance. It is a powerful solution."
"The feature that I have found most valuable for Alteryx is its geo-referencing feature, it is very good. I use it a lot, especially for supply chain."
"I think the most valuable feature for Alteryx in a health facility is that it permits cleaning, organizing, and merging of databases such as Excel and Access."
"Valuable features include visual workflow creation, workflow variables (parameterisation), automatic caching of all intermediate data sets in the workflow, scheduling with the server."
"The visual workflow tools for custom and complex tasks always beat raw coding languages with the agility, speed to deliver, and ease of subsequent changes."
"KNIME is quite scalable, which is one of the most important features that we found."
"It provides very fast problem solving and I don't need to do much coding in it. I just drag and drop."
"This solution is easy to use and it can be used to create any kind of model."
"Stability is excellent. I would give it a nine out of ten."
"Clear view of the data at every step of ETL process enables changing the flow as needed."
"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."
"Sometimes, there are performance constraints. Especially when a large file has to be ingested, the system slows down a bit. Its performance is the only thing that can be improved."
"The event handling, such that the file system watcher, is in need of improvement."
"It seems to me that it is not always user friendly."
"The formula we currently use in Alteryx can be automated."
"Deep learning models are not currently supported."
"It is a little bit pricey."
"Sometimes workflows tend to queue up, and they tend to get canceled for some reason that we don't know sometimes."
"The server is too expensive for what you get and it really a designer desktop on a server."
"The solution is inconvenient when it comes to wrangling data that includes multiple steps or features because each step or feature requires its own icon."
"They could add more detailed examples of the functionality of every node, how it works and how we can use it, to make things easier at the beginning."
"The most difficult part of the solution revolves around its areas concerning machine learning and deep learning."
"There should be better documentation and the steps should be easier."
"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."
"The program is not fit for handling very large files or databases (greater than 1GB); it gets too slow and has a tendency to crash easily."
"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."
"KNIME is not scalable."
Alteryx is ranked 3rd in Data Science Platforms with 74 reviews while KNIME is ranked 4th in Data Science Platforms with 50 reviews. Alteryx is rated 8.4, while KNIME is rated 8.2. The top reviewer of Alteryx writes "Feature-rich ETL that condenses a number of functions into one tool". On the other hand, the top reviewer of KNIME writes "A low-code platform that reduces data mining time by linking script". Alteryx is most compared with Dataiku, Databricks, RapidMiner, Tableau and Microsoft Power BI, whereas KNIME is most compared with RapidMiner, Microsoft Power BI, Dataiku, Weka and Microsoft Azure Machine Learning Studio. See our Alteryx vs. KNIME report.
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Of those three you should consider alteryx, it saves time in ETL a lot, Alteryx is better at handling large data sets tan Knime and RapidMiner. But please also consider Dataiku... Up to 3 users it's free ;o)