We performed a comparison between Alteryx 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."The cloud deployment ensures it scales easily."
"The design portion of this tool is easy to use without code, which his something that something we can appreciate."
"The drag-and-drop functionality, the ready-to-use analytics module, and the ability to track my data pipelines visually are the solution's most valuable features."
"The value add of Alteryx is the agility for making changes, and speed of deployment."
"The GUI is simple and it integrates with Python."
"There are a lot of good customization capabilities."
"Alteryx makes it easy for the end customer to see clean data in a structured form."
"Predictive models, which are easy to use, and help a lot with fast design and deployment."
"IBM was chosen because of usability. It's point and click, whereas the other out-of-the box-solution, or open-source solutions, require full-on programming and a much higher skill level."
"Stability is good."
"You take two quarters and compare them and this tool is ideal because it gives you a lot of visibility on the before and after."
"We have full control of the data handling process."
"The quality is very good."
"It makes pretty good use of memory. There are algorithms take a long time to run in R, and somehow they run more efficiently in Modeler."
"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."
"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."
"Its most valuable feature lies in its functionality."
"What they're struggling with is it's not as mature as Tableau in the user management area. It was tougher to manage the server part of it right away, especially since the user base has grown."
"Alteryx's development environment could be improved as it requires installation locally and can't be developed in the cloud."
"Configuration is very low."
"There are a few imputation techniques which they really need to include."
"Sometimes, there are performance constraints. Especially when a large file has to be ingested, the system slows down a bit. Its performance is the only thing that can be improved."
"The data integration component could most likely be improved to increase enterprise scalability."
"The solution is improving continuously. They have, for example, just added automatic insights. If they continue to improve on their overall service offering, that would be ideal."
"Neural networks are quite simple, and now neural networks are evolving to these architecture related to deep learning, etc. They didn't incorporate this in IBM SPSS Modeler."
"Requires more development."
"Dimension reduction should be classified separately."
"I would like see more programming languages added, like MATLAB. That would be better."
"It would be good if IBM added help resources to the interface."
"I think mapping for geographic data would also be a really great thing to be able to use."
"We would like to see better visualizations and easier integration with Cognos Analytics for reporting."
"The standard package (personal) is not supported for database connection."
Alteryx is ranked 3rd in Data Science Platforms with 29 reviews while IBM SPSS Modeler is ranked 11th in Data Science Platforms with 6 reviews. Alteryx is rated 8.4, while IBM SPSS Modeler is rated 8.0. The top reviewer of Alteryx writes "Allows you to organize, document workflows, low-code capabilities, and quick data processing speed". On the other hand, the top reviewer of IBM SPSS Modeler writes "Useful visual programming, minimal configuration required, and overall powerful". Alteryx is most compared with KNIME, Databricks, Dataiku Data Science Studio, RapidMiner and Starburst Enterprise, whereas IBM SPSS Modeler is most compared with KNIME, Microsoft Power BI, RapidMiner, IBM SPSS Statistics and SAS Enterprise Miner. See our Alteryx vs. IBM SPSS Modeler report.
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There are some important differences between both products. So probably, the first question I'll ask you is "for what use case are you evaluating these products?"
Of course, there are some general differences, starting with the T.C.O. and functionalities.
Alteryx is a code-free and code-friendly platform that allows you to tackle the whole cycle of your data, starting on the consumption from any source, through a drag and drop interface, very suitable for any user (I really don't see many HHRR's people using SPSS).
Both tackle the predictive modeling very well, while Alteryx allows you to feed several additional AI&ML platforms, like H2O, DataRobot, Thoughspot, MS, Google, Amazon, and even Watson). I'm not sure if SPSS allows you to build and publish models on so many platforms.
Alteryx is an extremely easy and flexible data tool, flexible in terms of drag and drop toolset and also has python, R integrations if your team requires this.
It can handle over 2 billion rows of data in its in-memory engine on a notebook without requiring a server, thus it's cheaper. It has a much better community than IBM that you can get your answers pretty clear and fast if you need it.
I am not familiar with IBM SPSS Modeler, therefore, I cannot compare these two products.
Regarding Alteryx I can say the following:
- An excellent desktop tool for Data Prep and analytics.
- Feature-rich and convenient user interface.
- However, it is implemented in C#, therefore works in MS Windows environment only. Mac or Linux users can’t use it. Interface with Apache Spark implemented via special plugin (do not remember details), which results in 2-hop data transfer. It may negatively affect performance.
I am unfamiliar with the IBM SPSS Modeler but use KNIME and Alteryx for different projects. Alteryx is an excellent, very easy to get started with and get to results data cleansing, ETL, analytics, geospatial modeling, predictive analytics. I build reusable macros in Alteryx, use flexible inputs for what-if modeling, feed information to Power BI or Tableau. It seems price competitive against SPSS.