We performed a comparison between Amazon SageMaker 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."The few projects we have done have been promising."
"The tool has made client management easier where patients need to upload their health records and we can use the tool to understand details on treatment date, amount, etc."
"Allows you to create API endpoints."
"I have contacted the solution's technical support, and they were really good. I rate the technical support a ten out of ten."
"The tool makes our ML model development a bit more efficient because everything is in one environment."
"The most valuable feature of Amazon SageMaker for me is the model deployment service."
"The superb thing that SageMaker brings is that it wraps everything well. It's got the deployment, the whole framework."
"We've had no problems with SageMaker's stability."
"It has allowed us to easily implement advanced analytics into various processes."
"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."
"We can deploy the solution in a cluster as well."
"We leverage KNIME flexibility in order to query data from our database and manipulate them for any ad-hoc business case, before presenting results to stakeholders."
"What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."
"From a user-friendliness perspective, it's a great tool."
"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."
"Easy to connect with every database: We use queries from SQL, Redshift, Oracle."
"The solution needs to be cheaper since it now charges per document for extraction."
"The solution is complex to use."
"SageMaker would be improved with the addition of reporting services."
"Amazon SageMaker could improve in the area of hyperparameter tuning by offering more automated suggestions and tips during the tuning process."
"Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."
"In general, improvements are needed on the performance side of the product's graphical user interface-related area since it consumes a lot of time for a user."
"The pricing of the solution is an issue...In SageMaker, monitoring could be improved by supporting more data types other than JSON and CSV."
"I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time."
"The data visualization part is the area most in need of improvement."
"It could input more data acquisitions from other sources and it is difficult to combine with Python."
"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'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."
"In the last update, KNIME started hiding a lot of the nodes. It doesn't mean hiding, but you need to know what you're looking for. Before that, you had just a tree that you could click, and you could get an overview of what kind of nodes do I have. Right now, it's like you need to know which node you need, and then you can start typing, but it's actually more difficult to find them."
"There should be better documentation and the steps should be easier."
"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."
"KNIME could improve when it comes to large data markets."
Amazon SageMaker is ranked 5th in Data Science Platforms with 18 reviews while KNIME is ranked 4th in Data Science Platforms with 50 reviews. Amazon SageMaker is rated 7.2, while KNIME is rated 8.2. The top reviewer of Amazon SageMaker writes "Easy to use and manage, but the documentation does not have a lot of information". On the other hand, the top reviewer of KNIME writes "A low-code platform that reduces data mining time by linking script". Amazon SageMaker is most compared with Databricks, Azure OpenAI, Google Vertex AI, Domino Data Science Platform and H2O.ai, whereas KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Weka and Tableau. See our Amazon SageMaker vs. KNIME report.
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