We performed a comparison between Dataiku and TIBCO Data Science 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."If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"The most valuable feature is the set of visual data preparation tools."
"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."
"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."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"The solution is quite stable."
"Data Science Studio's data science model is very useful."
"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 ease of setting up visualizations."
"The idea that you don't have to generate reports each day but they are sent automatically is great."
"We like the way we can drill down into each report to get back data on each project. From the portfolio level, I can see what is happening on it. That is a really important feature. I can look at indirect costs, for example, which are hitting each CIO portfolio. It's good to be able to see actual resources in terms of time as well as cost."
"The most valuable feature is the performance."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"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."
"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."
"I think it would help if Data Science Studio added some more features and improved the data model."
"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."
"The scripting for customization could be improved."
"Additional templates would help to get things moving more quickly in terms of getting the reports out."
"I would like the visualization for the map of countries to be more easily configurable."
"In terms of performance, I can see there are some issues when you are working with big data. When we are taking it from the Data Lake, we have a lot of issues."
Earn 20 points
Dataiku is ranked 11th in Data Science Platforms with 7 reviews while TIBCO Data Science is ranked 25th in Data Science Platforms. Dataiku is rated 8.2, while TIBCO Data Science is rated 7.6. The top reviewer of Dataiku writes "The model is very useful". On the other hand, the top reviewer of TIBCO Data Science writes "A straightforward initial setup and good reporting but needs better documentation". Dataiku is most compared with Databricks, KNIME, Alteryx, RapidMiner and Microsoft Azure Machine Learning Studio, whereas TIBCO Data Science is most compared with TIBCO Statistica, Amazon SageMaker and MathWorks Matlab. See our Dataiku vs. TIBCO Data Science report.
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