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 is a scalable solution. It is the largest advantage of the solution."
"Easy to use and requires minimal coding and customizations."
"Databricks helps crunch petabytes of data in a very short period of time."
"It is a cost-effective solution."
"Databricks gives you the flexibility of using several programming languages independently or in combination to build models."
"Databricks allows me to automate the creation of a cluster, optimized for machine learning and construct AI machine learning models for the client."
"We have the ability to scale, collaborate and do machine learning."
"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."
"It helped me in that I didn't need to write them by hand, and I could get a result in one or two minutes. That helped me a lot."
"It is a great product for running statistical analysis."
"The visual modeling capability is one of its attractive features."
"The most valuable features of the IBM SPSS Modeler are visual programming, you don't have to write any code, and it is easy to use. 90 to 95 percent of the use cases, you don't have to fine-tune anything. If you want to do something deeper, for example, create a better neural network, then you have to go into the features and try to fine-tune them. However, the default selection which is made by the tool, it's very practical and works well."
"Compared to other tools, the product works much easier to analyze data without coding."
"It's a very organized product. It's easy to use."
"Extremely easy to use, it offers a generous selection of proprietary machine learning algorithms."
"We have a local representative who specializes in SPSS. He will help us do the PoC."
"Would be helpful to have additional licensing options."
"The query plan is not easy with Databrick's job level. If I want to tune any of the code, it is not easily available in the blogs as well."
"I have had some issues with some of the Spark clusters running on Databricks, where the Spark runtime and clusters go up and down, which is an area for improvement."
"The solution has some scalability and integration limitations when consolidating legacy systems."
"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."
"There is room for improvement in the documentation of processes and how it works."
"The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment."
"It would be great if Databricks could integrate all the cloud platforms."
"Time Series or forecasting needs to be easier. It is a very important feature, and it should be made easier and more automated to use. For instance, for logistic regression, binary or multinomial is used automatically based on the type of the target variable. I wish they can make Time Series easier to use in a similar way."
"I would like see more programming languages added, like MATLAB. That would be better."
"I think mapping for geographic data would also be a really great thing to be able to use."
"It is very good, but slow. The slowness may be because we have not finalized all the background information in SPSS. It still needs some tweaking."
"The time series should be improved."
"The forecasting could be a bit easier."
"It's not as user friendly as it could be."
"We would like to see better visualizations and easier integration with Cognos Analytics for reporting."
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 Data Science Studio, 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 Data Science Studio. See our Databricks vs. IBM SPSS Modeler report.
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