H2O.ai vs Tom Sawyer Software Model-Based Engineering comparison

Cancel
You must select at least 2 products to compare!
H2O.ai Logo
1,962 views|1,376 comparisons
100% willing to recommend
Executive Summary

We performed a comparison between H2O.ai and Tom Sawyer Software Model-Based Engineering based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms.
To learn more, read our detailed Data Science Platforms Report (Updated: April 2024).
770,292 professionals have used our research since 2012.
Featured Review
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
  • "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."
  • More H2O.ai Pricing and Cost Advice →

    Information Not Available
    Ranking
    20th
    Views
    1,962
    Comparisons
    1,376
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    44th
    Views
    28
    Comparisons
    20
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    Buyer's Guide
    Data Science Platforms
    April 2024
    Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms. Updated: April 2024.
    770,292 professionals have used our research since 2012.
    Comparisons
    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.

    Generate and Customize MBSE Diagrams Instantly
    Twenty-first century design and manufacturing depend on digital transformation. That's why model-based systems engineering (MBSE) and diagram automation are taking off. See how we instantly transform your model definitions into rigorous, customized, user-friendly, and highly interactive visualizations. Watch a video.

    Sample Customers
    poder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco
    Information Not Available
    Top Industries
    VISITORS READING REVIEWS
    Financial Services Firm19%
    Computer Software Company11%
    Manufacturing Company9%
    Insurance Company6%
    No Data Available
    Company Size
    REVIEWERS
    Small Business22%
    Midsize Enterprise22%
    Large Enterprise56%
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise12%
    Large Enterprise70%
    No Data Available
    Buyer's Guide
    Data Science Platforms
    April 2024
    Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms. Updated: April 2024.
    770,292 professionals have used our research since 2012.

    H2O.ai is ranked 20th in Data Science Platforms while Tom Sawyer Software Model-Based Engineering is ranked 44th in Data Science Platforms. H2O.ai is rated 7.6, while Tom Sawyer Software Model-Based Engineering is rated 0.0. The top reviewer of H2O.ai writes "It is helpful, intuitive, and easy to use. The learning curve is not too steep". On the other hand, H2O.ai is most compared with Databricks, Amazon SageMaker, Dataiku Data Science Studio, Microsoft Azure Machine Learning Studio and KNIME, whereas Tom Sawyer Software Model-Based Engineering is most compared with .

    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.