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Amazon SageMaker vs IBM SPSS Statistics comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Amazon SageMaker
Ranking in Data Science Platforms
5th
Average Rating
7.8
Reviews Sentiment
9.1
Number of Reviews
29
Ranking in other categories
AI Development Platforms (4th)
IBM SPSS Statistics
Ranking in Data Science Platforms
10th
Average Rating
8.0
Number of Reviews
37
Ranking in other categories
Data Mining (3rd)
 

Mindshare comparison

As of November 2024, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 7.7%, down from 10.4% compared to the previous year. The mindshare of IBM SPSS Statistics is 2.8%, up from 2.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

Natu Lauchande - PeerSpot reviewer
Easy to use and manage, but the documentation does not have a lot of information
SageMaker Studio sounds very interesting. Feature Store and data pipeline features are very interesting. The product is a one-stop shop. It allows people without much engineering knowledge to try out and deploy models in environments similar to the production environments. The tool makes our ML model development a bit more efficient because everything is in one environment. It is easy to manage compared to when things were in different components of AWS. Amazon SageMaker is in AWS, so I need not pay two bills. It is one less system to manage, so it is easier.
AbakarAhmat - PeerSpot reviewer
Enhancing survey analysis that provides valued insightfulness
I used traditional tools where I would prepare data, click through menus, and use SQL Server for data visualization. We switched to IBM SPSS because it offers strong certification and aligns well with the standards we prioritize in our surveys. In terms of popularity, it stands out as the top choice in the market, especially in the research and university domains. Many different organizations and institutions use SPSS for statistical analytics. While there are other tools like MCLab and similar options available, SPSS is the most renowned and widely used among them.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Amazon SageMaker is highly valuable for managing ML workloads. It connects to AWS cloud resources, making it easy to deploy algorithms and collaborate using tools like GitLab. It offers a wide range of Python libraries and other necessary tools for modelling and algorithms."
"The feature I found most valuable is the data catalog, as it assists with the lineage of data through the preparation pipeline."
"The superb thing that SageMaker brings is that it wraps everything well. It's got the deployment, the whole framework."
"The product aggregates everything we need to build and deploy machine learning models in one place."
"The intuitive interface and streamlined user experience make it easy to navigate and set up various tools like Visual Studio Code or Jupyter Notebook."
"The most valuable feature of Amazon SageMaker is SageMaker Studio."
"They are doing a good job of evolving."
"The most valuable features are the ability to store artifacts and gather reports and measures from experiments."
"Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files."
"The most valuable features mainly include factor analysis, correlation analysis, and geographic analysis."
"in terms of the simplicity, I think the SPSS basic can handle it."
"It is a modeling tool with helpful automation."
"The solution is very comprehensive, especially compared to Minitabs, which is considered more for manufacturing. However, whatever data you want to analyze can be handled with SPSS."
"Most of the product features are good but I particularly like the linear regression analysis."
"SPSS can handle whatever you throw at it, whether your data set contains 10,000, 100,000, or a million objects. It's like the heavy artillery of analytical tools."
"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."
 

Cons

"The product must provide better documentation."
"In general, improvements are needed on the performance side of the product's graphical user interface-related area since it consumes a lot of time for a user."
"When starting a new session, the waiting time can be quite long, ranging from two to five minutes."
"Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."
"The solution requires a lot of data to train the model."
"Amazon might need to emphasize its capabilities in generative models more effectively."
"Amazon SageMaker can make it simpler to manage the data flow from start to finish, such as by integrating data, usingthe machine, and deploying models. This process could be more user-friendly compared to other tools. I would also like to improve integration with Bedrock and the LLM connection for AWS."
"The documentation must be made clearer and more user-friendly."
"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."
"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."
"This solution is not suitable for use with Big Data."
"Technical support needs some improvement, as they do not respond as quickly as we would like."
"The statistics should be more self-explanatory with detailed automated reports."
"IBM SPSS Statistics does not keep you close to your data like KNIME."
"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."
"In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options."
 

Pricing and Cost Advice

"Databricks solution is less costly than Amazon SageMaker."
"The product is expensive."
"You don't pay for Sagemaker. You only pay for the compute instances in your storage."
"In terms of pricing, I'd also rate it ten out of ten because it's been beneficial compared to other solutions."
"There is no license required for the solution since you can use it on demand."
"The pricing is complicated as it is based on what kind of machines you are using, the type of storage, and the kind of computation."
"On a scale from one to ten, where one is cheap, and ten is expensive, I rate the solution's pricing a six out of ten."
"The solution is relatively cheaper."
"It's quite expensive, but they do a special deal for universities."
"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."
"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."
"While the pricing of the product may be higher, the accompanying service and features justify the investment."
"SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced."
"Our licence is on a yearly renewal basis. While pricing is not the primary concern in our evaluation, as products are assessed by whether they can meet our user needs and expertise, the cost can be a limiting factor in the number of licences we procure."
"I rate the tool's pricing a five out of ten."
"More affordable training for new staff members."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Educational Organization
14%
Computer Software Company
11%
Manufacturing Company
8%
Financial Services Firm
17%
University
9%
Computer Software Company
9%
Manufacturing Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

How would you compare Databricks vs Amazon SageMaker?
We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...
What do you like most about Amazon SageMaker?
We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to ChatGPT that requires models. We utilize Amazon SageMaker to create endpoints for t...
What is your experience regarding pricing and costs for Amazon SageMaker?
The pricing is based on usage, and I find it reasonable for what we use it for.
What do you like most about IBM SPSS Statistics?
The software offers consistency across multiple research projects helping us with predictive analytics capabilities.
What is your experience regarding pricing and costs for IBM SPSS Statistics?
The cost of IBM SPSS Statistics is managed by organizations, not individual researchers. It is a very expensive product, despite being good.
What needs improvement with IBM SPSS Statistics?
IBM SPSS Statistics does not keep you close to your data like KNIME. In KNIME, at every stage, you can see the resulting file and annotate your trail of evidence. It takes you further from your dat...
 

Also Known As

AWS SageMaker, SageMaker
SPSS Statistics
 

Learn More

Video not available
 

Overview

 

Sample Customers

DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit
LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA
Find out what your peers are saying about Amazon SageMaker vs. IBM SPSS Statistics and other solutions. Updated: October 2024.
816,406 professionals have used our research since 2012.