We performed a comparison between Databricks and IBM SPSS Statistics 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 has helped us have a good presence in data."
"It's very simple to use Databricks Apache Spark."
"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."
"Databricks gives us the ability to build a lakehouse framework and do everything implicit to this type of database structure. We also like the ability to stream events. Databricks covers a broad spectrum, from reporting and machine learning to streaming events. It's important for us to have all these features in one platform."
"Imageflow is a visual tool that helps make it easier for business people to understand complex workflows."
"The ability to stream data and the windowing feature are valuable."
"Databricks' most valuable features are the workspace and notebooks. Its integration, interface, and documentation are also good."
"Databricks integrates well with other solutions."
"The most valuable features are the solution is easy to use, training new users is not difficult, and our usage is comprehensive because the whole service is beneficial."
"The most valuable features mainly include factor analysis, correlation analysis, and geographic analysis."
"SPSS is quite robust and quicker in terms of providing you the output."
"The most valuable feature is the user interface because you don't need to write code."
"Custom tables and macros: They allow us to create useful reports quickly for a broad audience."
"It has helped our analyst unit deliver work with more transparency and confidence, given that we can always view the dataset in totality, after each step of data transformation."
"The solution has numerous valuable features. We particularly like custom tabs. It's very useful. We end up analyzing a lot of software data, so features related to custom tabs are really helpful."
"in terms of the simplicity, I think the SPSS basic can handle it."
"Scalability is an area with certain shortcomings. The solution's scalability needs improvement."
"I would like to see more documentation in terms of how an end-user could use it, and users like me can easily try it and implement use cases."
"Databricks could improve in some of its functionality."
"CI/CD needs additional leverage and support."
"The Databricks cluster can be improved."
"Instead of relying on a massive instance, the solution should offer micro partition levels. They're working on it, however, they need to implement it to help the solution run more effectively."
"Databricks has added some alerts and query functionality into their SQL persona, but the whole SQL persona, which is like a role, needs a lot of development. The alerts are not very flexible, and the query interface itself is not as polished as the notebook interface that is used through the data science and machine learning persona. It is clunky at present."
"It's not easy to use, and they need a better UI."
"The technical support should be improved."
"The solution needs to improve forecasting using time series analysis."
"I would like SPSS to improve its integration with other data-filing IBM tools. I also think its duration with data, utilization, and graphics could be better."
"The statistics should be more self-explanatory with detailed automated reports."
"The design of the experience can be improved."
"It could allow adding color to data models to make them easier to interpret."
"I know that SPSS is a statistical tool but it should also include a little bit of analytical behavior. You can call it augmented analysis or predictive analysis. The bottom line is it should have more graphical and analytical capabilities."
"If there is any self-generation data collection plan (DCP), it would be helpful in gathering data. It would also be useful if there is a function to scale it up to, let's say, UiPath and have it consolidate and integrate into a UiPath solution."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while IBM SPSS Statistics is ranked 8th in Data Science Platforms with 36 reviews. Databricks is rated 8.2, while IBM SPSS Statistics 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 Statistics writes "Enhancing survey analysis that provides valued insightfulness". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku Data Science Studio, Microsoft Azure Machine Learning Studio and Dremio, whereas IBM SPSS Statistics is most compared with Alteryx, TIBCO Statistica, Microsoft Azure Machine Learning Studio, IBM SPSS Modeler and SAS Analytics. See our Databricks vs. IBM SPSS Statistics report.
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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.
