We performed a comparison between Databricks and IBM SPSS Modeler 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."Databricks integrates well with other solutions."
"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."
"The solution's features are fantastic and include interactive clusters that perform at top speed when compared to other solutions."
"It is a cost-effective solution."
"Databricks' most valuable features are the workspace and notebooks. Its integration, interface, and documentation are also good."
"The load distribution capabilities are good, and you can perform data processing tasks very quickly."
"The solution is an impressive tool for data migration and integration."
"The capacity of use of the different types of coding is valuable. Databricks also has good performance because it is running in spark extra storage, meaning the performance and the capacity use different kinds of codes."
"We had an IBM Guardium service contract where we used one of their resources to help us develop our prototype. It was a good experience, but they were helpful and responsive."
"We have full control of the data handling process."
"It gives you a GUI interface, which is a lot more user-friendly and easier to use compared to writing R scripts or Python."
"It is just a lot faster. So you do not have to write a bunch of code, you can throw that stuff on there pretty quickly and do prototyping quickly."
"The ease of use in the user interface is the best part of it. The ability to customize some of my streams with R and Python has been very useful to me, I've automated a few things with that."
"Our business units' capabilities with SPSS Modeler is high. They no longer waste time on modeling and algorithms, meaning they are not coding any more. For example, segmentation projects now take one to three months, rather than six months to a year, as before."
"New algorithms are added into every version of Modeler, e.g., SMOTE, random forest, etc. The Derive node is used for the syntax code to derive the data."
"We have integration where you can write third-party apps. This sort of feature opens it up to being able to do anything you want."
"Databricks is not geared towards the end-user, but rather it is for data engineers or data scientists."
"CI/CD needs additional leverage and support."
"There are no direct connectors — they are very limited."
"Doesn't provide a lot of credits or trial options."
"The pricing of Databricks could be cheaper."
"We'd like a more visual dashboard for analysis It needs better UI."
"The integration of data could be a bit better."
"This solution only supports queries in SQL and Python, which is a bit limiting."
"It would be good if IBM added help resources to the interface."
"The standard package (personal) is not supported for database connection."
"I think mapping for geographic data would also be a really great thing to be able to use."
"It would be helpful if SPSS supported open-source features, for example, embedding R or Python scripts in SPSS Modeler."
"If IBM could add some of the popular models into the SPSS for further analysis, like popular regression models, I think that would be a helpful improvement."
"When you are not using the product, such as during the pandemic where we had worldwide lockdowns, you still have to pay for the licensing."
"The time series should be improved."
"Expensive to deploy solutions. You need to buy an extra deployment unit."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while IBM SPSS Modeler is ranked 12th in Data Science Platforms with 38 reviews. Databricks is rated 8.2, while IBM SPSS Modeler is rated 8.0. The top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". On the other hand, the top reviewer of IBM SPSS Modeler writes "Easy to use, quick to learn, and offers many ways to analyze data". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku, Microsoft Azure Machine Learning Studio and Dremio, whereas IBM SPSS Modeler is most compared with KNIME, Microsoft Power BI, RapidMiner, IBM SPSS Statistics and Dataiku. See our Databricks vs. IBM SPSS Modeler report.
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