Compare Amazon SageMaker vs. H2O.ai

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Amazon SageMaker Logo
10,392 views|9,138 comparisons
H2O.ai Logo
7,624 views|5,023 comparisons
Most Helpful Review
Find out what your peers are saying about Amazon SageMaker vs. H2O.ai and other solutions. Updated: September 2020.
442,845 professionals have used our research since 2012.
Quotes From Members

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

Pros
"The few projects we have done have been promising.""They are doing a good job of evolving.""The most valuable feature of Amazon SageMaker is that you don't have to do any programming in order to perform some of your use cases.""Allows you to create API endpoints.""The deployment is very good, where you only need to press a few buttons."

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"It is helpful, intuitive, and easy to use. The learning curve is not too steep.""The ease of use in connecting to our cluster machines.""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.""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."

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Cons
"I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time.""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.""AI is a new area and AWS needs to have an internship training program available.""Lacking in some machine learning pipelines.""Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."

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"The model management features could be improved.""I would like to see more features related to deployment.""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.""On the topic of model training and model governance, this solution cannot handle ten or twelve models running at the same time."

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Pricing and Cost Advice
"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.""The support costs are 10% of the Amazon fees and it comes by default."

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"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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Questions from the Community
Top Answer: Allows you to create API endpoints.
Top Answer: The pricing for the Notebook endpoints is a bit high, but generally reasonable.
Top Answer: The product has come a long way and they've added a lot of things, but in terms of improvement I would like to probably have features such as MLflow embedded into it. Additional features I would like… more »
Top Answer: 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.
Top Answer: On the topic of model training and model governance, this solution cannot handle ten or twelve models running at the same time. It becomes a problem. I would like to see better integration with Python… more »
Top Answer: I am a solution architect and a consultant, and I use H2O as a machine learning platform. I create ensemble models using R and H2O, tune the hyperparameters, and then deploy them. There are various… more »
Ranking
14th
Views
10,392
Comparisons
9,138
Reviews
4
Average Words per Review
510
Avg. Rating
7.5
12th
Views
7,624
Comparisons
5,023
Reviews
5
Average Words per Review
350
Avg. Rating
7.6
Popular Comparisons
Compared 29% of the time.
Compared 19% of the time.
Compared 10% of the time.
Compared 8% of the time.
Also Known As
AWS SageMaker, SageMaker
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Amazon
H2O.ai
Overview

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.

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Learn more about Amazon SageMaker
Learn more about H2O.ai
Sample Customers
DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuitpoder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco
Top Industries
VISITORS READING REVIEWS
Computer Software Company32%
Media Company20%
Comms Service Provider9%
Insurance Company5%
VISITORS READING REVIEWS
Computer Software Company35%
Comms Service Provider14%
Media Company8%
Insurance Company7%
Company Size
REVIEWERS
Midsize Enterprise57%
Large Enterprise43%
REVIEWERS
Small Business13%
Midsize Enterprise25%
Large Enterprise63%
Find out what your peers are saying about Amazon SageMaker vs. H2O.ai and other solutions. Updated: September 2020.
442,845 professionals have used our research since 2012.
Amazon SageMaker is ranked 14th in Data Science Platforms with 5 reviews while H2O.ai is ranked 12th in Data Science Platforms with 5 reviews. Amazon SageMaker is rated 7.6, while H2O.ai is rated 7.6. The top reviewer of Amazon SageMaker writes "A solution with great computational storage, has many pre-built models, is stable, and has good support". On the other hand, the top reviewer of H2O.ai writes "It is helpful, intuitive, and easy to use. The learning curve is not too steep". Amazon SageMaker is most compared with Databricks, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio, Domino Data Science Platform and IBM Watson Studio, whereas H2O.ai is most compared with KNIME, Dataiku Data Science Studio, Microsoft Azure Machine Learning Studio, Alteryx and Databricks. See our Amazon SageMaker vs. H2O.ai report.

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