Amazon SageMaker vs Google Cloud Datalab comparison

Amazon Web Services (AWS) and Google are both solutions in the Data Science Platforms category. Amazon Web Services (AWS) is ranked #5 with an average rating of 7.6, while Google is ranked #15 with an average rating of 7.8. Amazon Web Services (AWS) holds a 7.7% mindshare in Data Science Platforms, compared to Google’s 1.0% mindshare. Additionally, 89% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 80% of Google users who would recommend it.

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Executive Summary

We performed a comparison between Amazon SageMaker and Google Cloud Datalab 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.

To learn more, read our detailed Amazon SageMaker vs. Google Cloud Datalab Report (Updated: October 2024).

Buyer's Guide

Amazon SageMaker vs. Google Cloud Datalab

October 2024

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Helped 816,406 peers since 2012

Categories and Ranking

IBM SPSS Statistics

Mindshare comparison

As of November 2024, in the Data Science Platforms category, the mindshare of IBM SPSS Statistics is 2.8%, up from 2.6% compared to the previous year. The mindshare of Amazon SageMaker is 7.7%, down from 10.4% compared to the previous year. The mindshare of Google Cloud Datalab is 1.0%, down from 1.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

AbakarAhmat

Software Engineer at a university with 10,001+ employees

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.

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Natu Lauchande

Tech Lead - Sanlam Fintech Cluster - Data,ML,AI Eng. at Sanlam

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.

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Nilesh Gode

Project Manager - Data Science at Mettler-Toledo International Inc.

Easy to setup, stable and easy to design data pipelines

The scalability is average. We have not faced any issues with scalability. There are more than 500 end users using this solution in our company. It is an integral part of the daily operations. The usage pattern is not a one-time thing; employees regularly access and utilize the application. We use it at a global level with a scattered user base. This means that users don't all use the application at the same time. So, around 300 out of 500 employees use the solution, and this usage is spread out throughout the day.

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Quotes from Members

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

Pros

"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."

"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."

"in terms of the simplicity, I think the SPSS basic can handle it."

"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 learning curve to using this product is not steep. The program is appropriate for those who do not have a lot of background in programming, yet have to perform basic statistical analysis."

"The most valuable feature is its robust statistical analysis capabilities."

"The most valuable feature is the user interface because you don't need to write code."

"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."

More IBM SPSS Statistics pros

"The solution's ability to improve work at my organization stems from the ensemble model and a combination of various models it provides."

"The solution is easy to scale...The documentation and online community support have been sufficient for us so far."

"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 these models, making accessing them convenient as needed."

"The tool has made client management easier where patients need to upload their health records and we can use the tool to understand details on treatment date, amount, etc."

"Allows you to create API endpoints."

"Feature Store, CodeCommit, versioning, model control, and CI/CD pipelines are the most valuable features in Amazon SageMaker."

"The deployment is very good, where you only need to press a few buttons."

"The few projects we have done have been promising."

More Amazon SageMaker pros

"Google Cloud Datalab is very customizable."

"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."

"All of the features of this product are quite good."

"For me, it has been a stable product."

"The APIs are valuable."

"The infrastructure is highly reliable and efficient, contributing to a positive experience."

Cons

"The design of the experience can be improved."

"SPSS is a tool that's been around since the late 60s, and it's the universal worldwide standard for quantitative social science data analysis. That said, it does seem a bit strange to me that the graphical output functions are so clunky after all these years. The output of charts and graphs that SPSS produces is hideous."

"IBM SPSS Statistics does not keep you close to your data like KNIME."

"Needs more statistical modelling functions."

"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."

"It could allow adding color to data models to make them easier to interpret."

"Improvements are needed in the user interface, particularly in terms of user-friendliness."

"Better documentation on how to use macros."

More IBM SPSS Statistics cons

"SageMaker would be improved with the addition of reporting services."

"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."

"While integration is available, there are concerns about how secure this integration is, particularly when exposing data to SageMaker."

"Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."

"The training modules could be enhanced. We had to take in-person training to fully understand SageMaker, and while the trainers were great, I think more comprehensive online modules would be helpful."

"The payment and monitoring metrics are a bit confusing not only for Amazon SageMaker but also for the range of other products that fall under AWS, especially for a new user of the product."

"Amazon SageMaker could improve in the area of hyperparameter tuning by offering more automated suggestions and tips during the tuning process."

"When starting a new session, the waiting time can be quite long, ranging from two to five minutes."

More Amazon SageMaker cons

"The product must be made more user-friendly."

"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."

"Even if your application is always connected to its database, the processing can be cumbersome. It shouldn't be so complicated."

"There is room for improvement in the graphical user interface. So that the initial user would use it properly, that would be a good option."

"We have also encountered challenges during our transition period in terms of data control and segmentation. The management of each channel and data structure as it has its own unique characteristics requires very detailed and precise control. The allocation should be appropriate and the complexity increases due to the different time zones and geographic locations of our clients. The process usually involves migrating the existing database sets to gcp and ensure data integrity is maintained. This is the only challenge that we faced while navigating the integers of the solution and honestly it was an interesting and unique experience."

"The interface should be more user-friendly."

Pricing and Cost Advice

"It's quite expensive, but they do a special deal for universities."

"I rate the tool's pricing a five out of ten."

"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."

"The price of IBM SPSS Statistics could improve."

"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."

"We think that IBM SPSS is expensive for this function."

"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."

More IBM SPSS Statistics pricing and cost advice

"There is no license required for the solution since you can use it on demand."

"SageMaker is worth the money for our use case."

"I would rate the solution's price a ten out of ten since it is very high."

"In terms of pricing, I'd also rate it ten out of ten because it's been beneficial compared to other solutions."

"The pricing is comparable."

"The product is expensive."

"I rate the pricing a five on a scale of one to ten, where one is the lowest price, and ten is the highest price. The solution is priced reasonably. There is no additional cost to be paid in excess of the standard licensing fees."

"You don't pay for Sagemaker. You only pay for the compute instances in your storage."

More Amazon SageMaker pricing and cost advice

"It is affordable for us because we have a limited number of users."

"The product is cheap."

"The pricing is quite reasonable, and I would give it a rating of four out of ten."

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

University

Computer Software Company

Manufacturing Company

Financial Services Firm

18%

Educational Organization

14%

Computer Software Company

11%

Manufacturing Company

Financial Services Firm

20%

Computer Software Company

14%

University

10%

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about IBM SPSS Statistics?

The software offers consistency across multiple research projects helping us with predictive analytics capabilities.

See all answers

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 produ...

See all answers

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 result...

See all answers

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 designe...

See all answers

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 Cha...

See all answers

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.

See all answers

What do you like most about Google Cloud Datalab?

Google Cloud Datalab is very customizable.

See all answers

What needs improvement with Google Cloud Datalab?

Access is always via URL, and unless your network is fast, it would be a little tough in India. In India, if we had a...

See all answers

What is your primary use case for Google Cloud Datalab?

It's for our daily data processing, and there's a batch job that executes it. The process involves more than ten serv...

See all answers

Comparisons

IBM SPSS Modeler vs IBM SPSS Statistics

Compared 14% of the time

Alteryx vs IBM SPSS Statistics

Compared 14% of the time

TIBCO Statistica vs IBM SPSS Statistics

Compared 13% of the time

Microsoft Azure Machine Learning Studio vs IBM SPSS Statistics

Compared 12% of the time

SAS Analytics vs IBM SPSS Statistics

Compared 4% of the time

More IBM SPSS Statistics Competitors

Databricks vs Amazon SageMaker

Compared 27% of the time

Azure OpenAI vs Amazon SageMaker

Compared 12% of the time

Google Vertex AI vs Amazon SageMaker

Compared 11% of the time

Domino Data Science Platform vs Amazon SageMaker

Compared 7% of the time

Dataiku vs Amazon SageMaker

Compared 6% of the time

More Amazon SageMaker Competitors

Databricks vs Google Cloud Datalab

Compared 25% of the time

Cloudera Data Science Workbench vs Google Cloud Datalab

Compared 19% of the time

IBM SPSS Modeler vs Google Cloud Datalab

Compared 10% of the time

KNIME vs Google Cloud Datalab

Compared 9% of the time

Microsoft Azure Machine Learning Studio vs Google Cloud Datalab

Compared 8% of the time

More Google Cloud Datalab Competitors

Product Reports

Buyer's Guide

IBM SPSS Statistics

November 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Amazon SageMaker

November 2024

Download Amazon SageMaker product report

Buyer's Guide

Google Cloud Datalab

November 2024

Download Google Cloud Datalab product report

Also Known As

SPSS Statistics

AWS SageMaker, SageMaker

No data available

Learn More

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IBM

Amazon Web Services (AWS)

Google

Overview

IBM SPSS Statistics is a powerful data mining solution that is designed to aid business leaders in making important business decisions. It is designed so that it can be effectively utilized by organizations across a wide range of fields. SPSS Statistics allows users to leverage machine learning algorithms so that they can mine and analyze data in the most effective way possible.

IBM SPSS Statistics Benefits

Some of the ways that organizations can benefit by choosing to deploy IBM SPSS Statistics include:

Ease of use. SPSS Statistics enables users to simply and intuitively take control of their statistical needs. The solution is designed so that analysts who do not know how to code can easily make full use of the various tools and capabilities that SPSS Statistics has to offer. Its command language is so straightforward that it does not require users to undergo special training before they use it.

Comprehensive and flexible build. SPSS Statistics is designed to be both a comprehensive and highly flexible analytics solution. It enables users to utilize a variety of integrations that make it easy for users to add features that they might feel they are missing.

Automation. SPSS Statistics makes it simple for users to automate basic tasks that they might otherwise devote too much time worrying about. Tasks like calculation or data gathering can be delegated to the system while more conceptual tasks like data analysis are given to an organization’s analysts to handle.

IBM SPSS Statistics Features

Intuitive user interface. SPSS Statistics enables users to deploy an intuitive interface that makes the process of system management simple. Among the other components of this interface is a drag-and-drop feature that makes analysis and management possible for anyone who wants to use it.

Advanced data visualizations. Analysts that employ SPSS Statistics gain access to tools that empower them to create and export data visualizations. These visualizations can be formatted in many different ways depending on what the user needs.

Local data storage. SPSS Statistics has the ability to securely store data on a user’s computer. This enables them to add layers of security that would not necessarily be present if the data was stored in the cloud.

Reviews from Real Users

IBM SPSS Statistics is a highly effective solution that stands out when compared to many of its competitors. Two major advantages it offers are the wealth of functionalities that it provides and its high level of accessibility.

An Emeritus Professor of Health Services Research at a university writes, "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 in a multidimensional setup space. It's the multidimensional space facility that is most useful."

A Director of Systems Management & MIS Operations at a university, says, “The SPSS interface is very accessible and user-friendly. It's really easy to get information from it. I've shared it with experts and beginners, and everyone can navigate it.”

Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.

Cloud Datalab is a powerful interactive tool created to explore, analyze, transform and visualize data and build machine learning models on Google Cloud Platform. It runs on Google Compute Engine and connects to multiple cloud services easily so you can focus on your data science tasks.

Sample Customers

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

DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit

Information Not Available

Buyer's Guide

Amazon SageMaker vs. Google Cloud Datalab

October 2024

Free Report: Amazon SageMaker vs. Google Cloud Datalab

Find out what your peers are saying about Amazon SageMaker vs. Google Cloud Datalab and other solutions. Updated: October 2024.

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