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' most valuable feature is the data transformation through PySpark."
"Databricks is a scalable solution. It is the largest advantage of the solution."
"Its lightweight and fast processing are valuable."
"Databricks has improved my organization by allowing us to transform data from sources to a different format and feed that to the analytics, business intelligence, and reporting teams. This tool makes it easy to do those kinds of things."
"This solution offers a lake house data concept that we have found exciting. We are able to have a large amount of data in a data lake and can manage all relational activities."
"When we have a huge volume of data that we want to process with speed, velocity, and volume, we go through Databricks."
"I haven't heard about any major stability issues. At this time I feel like it's stable."
"The ease of use and its accessibility are valuable."
"One feature I found very valuable was the analysis of variance (ANOVA)."
"in terms of the simplicity, I think the SPSS basic can handle it."
"Capability analysis is one of the main and valuable functions. We also do some hypothesis testing in Minitab and summary stats. These are the functions that we find very useful."
"The most valuable feature is the user interface because you don't need to write code."
"IBM SPSS Statistics depends on AI."
"You can find a complete algorithm in the solution and use it. You don't need to write your own algorithms for predictive analytics. That's the most valuable feature and the main one we use."
"The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can into multidimensional setup space. It's the multidimensional space facility that is most useful."
"They have many existing algorithms that we can use and use effectively to analyze and understand how to put our data to work to improve what we do."
"Scalability is an area with certain shortcomings. The solution's scalability needs improvement."
"The data visualization for this solution could be improved. They have started to roll out a data visualization tool inside Databricks but it is in the early stages. It's not comparable to a solution like Power BI, Luca, or Tableau."
"Pricing is one of the things that could be improved."
"I would like more integration with SQL for using data in different workspaces."
"When I used the support, I had communication problems because of the language barrier with the agent. The accent was difficult to understand."
"Overall it's a good product, however, it doesn't do well against any individual best-of-breed products."
"It would be nice to have more guidance on integrations with ETLs and other data quality tools."
"Anyone who doesn't know SQL may find the product difficult to work with."
"I feel that when it comes to conducting multiple analyses, there could be more detailed information provided. Currently, the software gives a summary and an overview, but it would be beneficial to have specific details for each product or variable."
"The solution needs to improve forecasting using time series analysis."
"The solution could improve by providing a visual network for predictions and a self-organizing map for clustering."
"I'd like to see them use more artificial intelligence. It should be smart enough to do predictions and everything based on what you input."
"Most of the package will give you the fixed value, or the p-value, without an explanation as to whether it it significant or not. Some beginners might need not just the results, but also some explanation for them."
"IBM SPSS Statistics could improve the visual outputs where you are producing, for example, a graph for a company board of directors, or an advert."
"There is a learning curve; it's not very steep, but there is one."
"In some cases, the product takes time to load a large dataset. They could improve this particular area."
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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