H2O.ai vs TIBCO Data Science comparison

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H2O.ai Logo
2,121 views|1,487 comparisons
TIBCO Logo
509 views|395 comparisons
Executive Summary

We performed a comparison between H2O.ai and TIBCO Data Science 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: March 2024).
765,386 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:
Pros
"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 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.""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.""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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"The most valuable feature is the performance.""The idea that you don't have to generate reports each day but they are sent automatically is great.""The most valuable feature is the ease of setting up visualizations.""We like the way we can drill down into each report to get back data on each project. From the portfolio level, I can see what is happening on it. That is a really important feature. I can look at indirect costs, for example, which are hitting each CIO portfolio. It's good to be able to see actual resources in terms of time as well as cost."

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Cons
"It lacks the data manipulation capabilities of R and Pandas DataFrames. We would kill for dplyr offloading H2O.""The model management features could be improved.""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.""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.""I would like to see more features related to deployment.""It needs a drag and drop GUI like KNIME, for easy access to and visibility of workflows."

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"I would like the visualization for the map of countries to be more easily configurable.""Additional templates would help to get things moving more quickly in terms of getting the reports out.""In terms of performance, I can see there are some issues when you are working with big data. When we are taking it from the Data Lake, we have a lot of issues.""The scripting for customization could be improved."

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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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    Information Not Available
    Ranking
    19th
    Views
    2,121
    Comparisons
    1,487
    Reviews
    0
    Average Words per Review
    0
    Rating
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    25th
    Views
    509
    Comparisons
    395
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    Buyer's Guide
    Data Science Platforms
    March 2024
    Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms. Updated: March 2024.
    765,386 professionals have used our research since 2012.
    Comparisons
    Also Known As
    Alpine Data Chorus
    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.

    TIBCO Spotfire Data Science is an enterprise big data analytics platform that can help your organization become a digital leader. The collaborative user-interface allows data scientists, data engineers, and business users to work together on data science projects. These cross-functional teams can build machine learning workflows in an intuitive web interface with a minimum of code, while still leveraging the power of big data platforms.

    Sample Customers
    poder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco
    Havas Media, Tipping Point Community, eviCore
    Top Industries
    VISITORS READING REVIEWS
    Financial Services Firm19%
    Computer Software Company10%
    Manufacturing Company8%
    Insurance Company6%
    VISITORS READING REVIEWS
    Financial Services Firm18%
    Manufacturing Company15%
    Computer Software Company15%
    Pharma/Biotech Company10%
    Company Size
    REVIEWERS
    Small Business22%
    Midsize Enterprise22%
    Large Enterprise56%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise12%
    Large Enterprise71%
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise10%
    Large Enterprise71%
    Buyer's Guide
    Data Science Platforms
    March 2024
    Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms. Updated: March 2024.
    765,386 professionals have used our research since 2012.

    H2O.ai is ranked 19th in Data Science Platforms while TIBCO Data Science is ranked 25th in Data Science Platforms. H2O.ai is rated 7.6, while TIBCO Data Science is rated 7.6. 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, the top reviewer of TIBCO Data Science writes "A straightforward initial setup and good reporting but needs better documentation". H2O.ai is most compared with Amazon SageMaker, Databricks, Dataiku Data Science Studio, Microsoft Azure Machine Learning Studio and KNIME, whereas TIBCO Data Science is most compared with TIBCO Statistica, MathWorks Matlab, Amazon SageMaker and Dataiku Data Science Studio.

    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.