We performed a comparison between Amazon SageMaker and Dataiku 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 most valuable feature of Amazon SageMaker is its integration. For example, AWS Lambda. Additionally, we can write Python code."
"We were able to use the product to automate processes."
"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."
"The solution is easy to scale...The documentation and online community support have been sufficient for us so far."
"The deployment is very good, where you only need to press a few buttons."
"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."
"The few projects we have done have been promising."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"The solution is quite stable."
"The most valuable feature is the set of visual data preparation tools."
"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."
"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."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"The training modules could be enhanced. We had to take in-person training to fully understand SageMaker, and while the trainers were great, I think more comprehensive online modules would be helpful."
"The solution requires a lot of data to train the model."
"The documentation must be made clearer and more user-friendly."
"AI is a new area and AWS needs to have an internship training program available."
"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."
"Lacking in some machine learning pipelines."
"The pricing of the solution is an issue...In SageMaker, monitoring could be improved by supporting more data types other than JSON and CSV."
"The product must provide better documentation."
"The ability to have charts right from the explorer would be an improvement."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"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."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"I think it would help if Data Science Studio added some more features and improved the data model."
"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."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
Amazon SageMaker is ranked 5th in Data Science Platforms with 19 reviews while Dataiku is ranked 7th in Data Science Platforms with 7 reviews. Amazon SageMaker is rated 7.4, while Dataiku 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 Dataiku writes "Gives different aspects of modeling approaches and good for multiple teams' collaboration". Amazon SageMaker is most compared with Databricks, Azure OpenAI, Google Vertex AI, Domino Data Science Platform and DataRobot, whereas Dataiku is most compared with Databricks, KNIME, Alteryx, RapidMiner and SAS Visual Analytics. See our Amazon SageMaker vs. Dataiku report.
See our list of best Data Science Platforms vendors.
We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
