Compare H2O.ai vs. Teradata Analytics

H2O.ai is ranked 5th in Data Science Platforms with 6 reviews while Teradata Analytics is ranked 28th in Business Intelligence (BI) Tools with 2 reviews. H2O.ai is rated 7.6, while Teradata Analytics is rated 7.0. 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, the top reviewer of Teradata Analytics writes "Streamlines formulating solutions based on SQL-like queries". H2O.ai is most compared with KNIME, Microsoft Azure Machine Learning Studio and Dataiku Data Science Studio, whereas Teradata Analytics is most compared with Teradata Vantage, KNIME and SAS Enterprise Miner.
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H2O.ai Logo
5,300 views|3,711 comparisons
Teradata Analytics Logo
850 views|643 comparisons
Most Helpful Review
Find out what your peers are saying about Alteryx, IBM, Knime and others in Data Science Platforms. Updated: October 2019.
372,374 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
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 ease of use in connecting to our cluster machines.It is helpful, intuitive, and easy to use. The learning curve is not too steep.AutoML helps in hands-free initial evaluations of efficiency/accuracy of ML algorithms.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.

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nPath has made journey/path analysis much easier.It has been fantastic for running complete data sets (no sampling required).Provides ease of formulating a solution based on SQL-like queries.

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Cons
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.The model management features could be improved.It needs a drag and drop GUI like KNIME, for easy access to and visibility of workflows.Referring to bullet-3 as well, H2O DataFrame manipulation capabilities are too primitive.It lacks the data manipulation capabilities of R and Pandas DataFrames. We would kill for dplyr offloading H2O.

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I would like to see more/better documentation. They also need to enhance analytic/data science algorithms.We have struggled with uptime. Some of the features need to be updated.I have found some problems with the figures depicted on graphs and figures shown, like scores which could not be negative but which were depicted as such.

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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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372,374 professionals have used our research since 2012.
Ranking
5th
Views
5,300
Comparisons
3,711
Reviews
6
Average Words per Review
294
Avg. Rating
7.7
Views
850
Comparisons
643
Reviews
2
Average Words per Review
248
Avg. Rating
7.0
Top Comparisons
Compared 26% of the time.
Compared 10% of the time.
Also Known As
Teradata Aster Analytics, Aster Analytics
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H2O.ai
Teradata
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.

Teradata Aster® Analytics Portfolio provides a suite of ready-to-use, multi-genre advanced analytics functions that empowers business users to uncover and operationalize non-intuitive insights. Teradata Aster Analytics includes the Aster Database, Aster Client and the Aster Portfolio that consists of SQL, SQL-MapReduce and Graph functions for multi-genre advanced analytics. These functions provide everything from data acquisition and preparation to analytic modeling and visualization.

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Sample Customers
poder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco
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Top Industries
VISITORS READING REVIEWS
Software R&D Company45%
Comms Service Provider11%
Financial Services Firm9%
Transportation Company7%
No Data Available
Find out what your peers are saying about Alteryx, IBM, Knime and others in Data Science Platforms. Updated: October 2019.
372,374 professionals have used our research since 2012.
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.
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