H2O.ai vs SAS Enterprise Miner comparison

Cancel
You must select at least 2 products to compare!
H2O.ai Logo
4,139 views|2,901 comparisons
SAS Logo
2,326 views|1,845 comparisons
Comparison Buyer's Guide
Executive Summary

We performed a comparison between H2O.ai and SAS Enterprise Miner based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Alteryx, Microsoft and others in Data Science Platforms.
To learn more, read our detailed Data Science Platforms Report (Updated: November 2022).
655,465 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:
Pricing and Cost Advice
Information Not Available
  • "The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it."
  • More SAS Enterprise Miner Pricing and Cost Advice →

    report
    Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.
    655,465 professionals have used our research since 2012.
    Questions from the Community
    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 »
    Top Answer:We're using Enterprise Guide simultaneously with Enterprise Miner. From my perspective, I believe that open-source analytics tools are closer to fitting our needs. We prefer open-source options like… more »
    Top Answer:I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically… more »
    Top Answer:The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it.
    Ranking
    15th
    Views
    4,139
    Comparisons
    2,901
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    13th
    Views
    2,326
    Comparisons
    1,845
    Reviews
    1
    Average Words per Review
    391
    Rating
    8.0
    Comparisons
    Also Known As
    Enterprise Miner
    Learn More
    Overview

    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.

    SAS Enterprise Miner is a solution to create accurate predictive and descriptive models on large volumes of data across different sources in the organization. SAS Enterprise Miner offers many features and functionalities for the business analysts to model their data. Some of the business applications are for detecting fraud, minimizing risk, resource demands, reducing asset downtime, campaigns and reduce customer attrition.
    Offer
    Learn more about H2O.ai
    Learn more about SAS Enterprise Miner
    Sample Customers
    poder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco
    Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare
    Top Industries
    VISITORS READING REVIEWS
    Computer Software Company20%
    Financial Services Firm14%
    Comms Service Provider11%
    Manufacturing Company6%
    REVIEWERS
    Financial Services Firm57%
    Media Company14%
    Retailer14%
    University14%
    VISITORS READING REVIEWS
    Financial Services Firm18%
    Computer Software Company13%
    Comms Service Provider10%
    University7%
    Company Size
    REVIEWERS
    Small Business22%
    Midsize Enterprise22%
    Large Enterprise56%
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise14%
    Large Enterprise71%
    REVIEWERS
    Small Business25%
    Midsize Enterprise33%
    Large Enterprise42%
    VISITORS READING REVIEWS
    Small Business19%
    Midsize Enterprise13%
    Large Enterprise68%
    Buyer's Guide
    Data Science Platforms
    November 2022
    Find out what your peers are saying about Databricks, Alteryx, Microsoft and others in Data Science Platforms. Updated: November 2022.
    655,465 professionals have used our research since 2012.

    H2O.ai is ranked 15th in Data Science Platforms while SAS Enterprise Miner is ranked 13th in Data Science Platforms with 1 review. H2O.ai is rated 0.0, while SAS Enterprise Miner is rated 8.0. On the other hand, the top reviewer of SAS Enterprise Miner writes "A comprehensive data analytics tool with several valuable features, satisfactory technical support, and a stable build". H2O.ai is most compared with Amazon SageMaker, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio, Databricks and KNIME, whereas SAS Enterprise Miner is most compared with SAS Visual Analytics, Microsoft Azure Machine Learning Studio, IBM SPSS Modeler, Alteryx and RapidMiner.

    See our list of best Data Science Platforms vendors.

    We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.