Amazon SageMaker vs H2O.ai comparison

Amazon Web Services (AWS) and H2O.ai are both solutions in the Data Science Platforms category. Amazon Web Services (AWS) is ranked #5 with an average rating of 7.6, while H2O.ai is ranked #22. Amazon Web Services (AWS) holds a 7.7% mindshare in Data Science Platforms, compared to H2O.ai’s 1.5% mindshare. Additionally, 89% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of H2O.ai users who would recommend it.

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Executive Summary

We performed a comparison between Amazon SageMaker and H2O.ai 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. H2O.ai Report (Updated: October 2024).

Buyer's Guide

Amazon SageMaker vs. H2O.ai

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 H2O.ai is 1.5%, up 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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Kashif Yaseen

Trainee Decision Scientist at a tech services company with 1,001-5,000 employees

Plug-and-play convenience enhances productivity but needs better multimodal support

We mostly used the solution in the domain that I'm working. We had most of the use cases around chatbots and conversational BI The solution was plug-and-play, meaning most of the components were handled by the solution itself rather than building them from scratch. This was useful for our banking…

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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

"You can quickly build models because it does the work for you."

"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."

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

"The SPSS interface is very accessible and user-friendly. It's really easy to get information in it. I've shared it with experts and beginners, and everyone can navigate 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."

"Custom tables and macros: They allow us to create useful reports quickly for a broad audience."

"The most valuable features mainly include factor analysis, correlation analysis, and geographic analysis."

"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."

More IBM SPSS Statistics pros

"SageMaker offers functionalities like Jupyter Notebooks for development, built-in algorithms, model tuning, and options to deploy models on managed infrastructure."

"It's user-friendly for business teams as they can understand many aspects through the AWS interface."

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

"We were able to use the product to automate processes."

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

"The Autopilot feature is really good because it's helpful for people who don't have much experience with coding or data pipelines. When we suggest SageMaker to clients, they don't have to go through all the steps manually. They can leverage Autopilot to choose variables, run experiments, and monitor costs. The results are also pretty accurate."

"The most valuable features are the ability to store artifacts and gather reports and measures from experiments."

"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."

More Amazon SageMaker pros

"The most valuable features are the machine learning tools, the support for Jupyter Notebooks, and the collaboration that allows you to share it across people."

"The ease of use in connecting to our cluster machines."

"Fast training, memory-efficient DataFrame manipulation, well-documented, easy-to-use algorithms, ability to integrate with enterprise Java apps (through POJO/MOJO) are the main reasons why we switched from Spark to H2O."

"The most valuable feature of H2O.ai is that it is plug-and-play."

"AutoML helps in hands-free initial evaluations of efficiency/accuracy of ML algorithms."

"It is helpful, intuitive, and easy to use. The learning curve is not too steep."

"One of the most interesting features of the product is their driverless component. The driverless component allows you to test several different algorithms along with navigating you through choosing the best algorithm."

Cons

"This solution is not suitable for use with Big Data."

"One of the areas that should be similar to Minitabs is the use of blogs. The Minitabs blog helps users understand the tools and gives lots of practical examples. Following the SPSS manual is cumbersome. It's a good, exhaustive manual, but it's not practical to use. With Minitabs, you can go to the blogs and find specific articles written about various components and it's very helpful. Without blogs, we find SPSS more complicated."

"The technical support should be improved."

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

"In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options."

"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."

"The product should provide more ways to import data and export results that are user-friendly for high-level executives."

"SPSS slows down the computer or the laptop if the data is huge; then you need a faster computer."

More IBM SPSS Statistics cons

"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."

"The documentation must be made clearer and more user-friendly."

"There are other better solutions for large data, such as Databricks."

"The platform could be more accessible to users with basic coding skills, making it more intuitive and easier for beginners to use comfortably."

"I would suggest that Amazon SageMaker provide free slots to allow customers to practice, such as a free slot to try out working with a Sandbox."

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

"The solution is complex to use."

"The product must provide better documentation."

More Amazon SageMaker cons

"H2O.ai can improve in areas like multimodal support and prompt engineering."

"I would like to see more features related to deployment."

"Referring to bullet-3 as well, H2O DataFrame manipulation capabilities are too primitive."

"On the topic of model training and model governance, this solution cannot handle ten or twelve models running at the same time."

"It needs a drag and drop GUI like KNIME, for easy access to and visibility of workflows."

"The model management features could be improved."

"The interpretability module has room for improvement. Also, it needs to improve its ability to integrate with other systems, like SageMaker, and the overall integration capability."

"It lacks the data manipulation capabilities of R and Pandas DataFrames. We would kill for dplyr offloading H2O."

Pricing and Cost Advice

"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."

"The price of this solution is a little bit high, which was a problem for my company."

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

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

"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."

"More affordable training for new staff members."

"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."

More IBM SPSS Statistics pricing and cost advice

"The pricing is comparable."

"The cost offers a pay-as-you-go pricing model. It depends on the instance that you do."

"The product is expensive."

"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 tool's pricing is reasonable."

"Amazon SageMaker is a very expensive product."

"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."

More Amazon SageMaker pricing and cost advice

"We have seen significant ROI where we were able to use the product in certain key projects and could automate a lot of processes. We were even able to reduce staff."

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816,406 professionals have used our research since 2012.

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

11%

Manufacturing Company

10%

Insurance Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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

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Comparisons

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Compared 14% of the time

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TIBCO Statistica vs IBM SPSS Statistics

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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

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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

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Databricks vs H2O.ai

Compared 21% of the time

Dataiku vs H2O.ai

Compared 19% of the time

Microsoft Azure Machine Learning Studio vs H2O.ai

Compared 14% of the time

KNIME vs H2O.ai

Compared 11% of the time

IBM Watson Studio vs H2O.ai

Compared 6% of the time

More H2O.ai 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

Data Science Platforms

November 2024

Download H2O.ai product report

Also Known As

SPSS Statistics

AWS SageMaker, SageMaker

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IBM

Amazon Web Services (AWS)

H2O.ai

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.

H2O is a fully open source, distributed in-memory machine learning platform with linear scalability. H2O’s supports the most widely used statistical & machine learning algorithms including gradient boosted machines, generalized linear models, deep learning and more. H2O also has an industry leading AutoML functionality that automatically runs through all the algorithms and their hyperparameters to produce a leaderboard of the best models. The H2O platform is used by over 14,000 organizations globally and is extremely popular in both the R & Python communities.

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

poder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco

Buyer's Guide

Amazon SageMaker vs. H2O.ai

October 2024

Free Report: Amazon SageMaker vs. H2O.ai

Find out what your peers are saying about Amazon SageMaker vs. H2O.ai and other solutions. Updated: October 2024.

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