Angoss KnowledgeENTERPRISE [EOL] vs H2O.ai comparison

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2,037 views|1,441 comparisons
100% willing to recommend
Executive Summary

We performed a comparison between Angoss KnowledgeENTERPRISE [EOL] and H2O.ai 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).
768,740 professionals have used our research since 2012.
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Pricing and Cost Advice
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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."
  • More H2O.ai Pricing and Cost Advice →

    Ranking
    Unranked
    In Data Science Platforms
    19th
    Views
    2,037
    Comparisons
    1,441
    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.
    768,740 professionals have used our research since 2012.
    Comparisons
    Also Known As
    KnowledgeENTERPRISE, Datawatch Angoss, Angoss KnowledgeENTERPRISE
    Learn More
    Overview

    KnowledgeENTERPRISE is a comprehensive data science platform that is integrated with Spark technology to provide unprecedented analytics and data processing capabilities. Its in-place analysis capability on distributed data eliminates data movement and allows users to stay within their Big Data environments.

    This single, fully-integrated software solution enables access to open source machine-learning libraries, Big Data technologies, collaboration and governance features, comprehensive advanced analytics functionality, and numerous deployment options allowing users to overcome challenges in Big Data ingestion, access, and results interpretation. 

    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
    Barclays, ANZ, Fidelity, Comcast, Rogers, T-Mobile, DirecTV
    poder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco
    Top Industries
    No Data Available
    VISITORS READING REVIEWS
    Financial Services Firm19%
    Computer Software Company11%
    Manufacturing Company8%
    Insurance Company5%
    Company Size
    No Data Available
    REVIEWERS
    Small Business22%
    Midsize Enterprise22%
    Large Enterprise56%
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise12%
    Large Enterprise70%
    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.
    768,740 professionals have used our research since 2012.

    Angoss KnowledgeENTERPRISE [EOL] doesn't meet the minimum requirements to be ranked in Data Science Platforms while H2O.ai is ranked 19th in Data Science Platforms. Angoss KnowledgeENTERPRISE [EOL] is rated 0.0, while H2O.ai is rated 7.6. 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". Angoss KnowledgeENTERPRISE [EOL] is most compared with Analance, whereas H2O.ai is most compared with Databricks, Amazon SageMaker, Dataiku Data Science Studio, Microsoft Azure Machine Learning Studio and KNIME.

    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.