Compare H2O.ai vs. IBM Watson Studio

H2O.ai is ranked 10th in Data Science Platforms with 7 reviews while IBM Watson Studio is ranked 9th in Data Science Platforms with 6 reviews. H2O.ai is rated 7.6, while IBM Watson Studio is rated 8.4. 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 IBM Watson Studio writes "It has greatly improved the performance because it is standardized across the company". H2O.ai is most compared with KNIME, Dataiku Data Science Studio and Microsoft Azure Machine Learning Studio, whereas IBM Watson Studio is most compared with IBM SPSS Modeler, Microsoft Azure Machine Learning Studio and Amazon SageMaker. See our H2O.ai vs. IBM Watson Studio report.
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H2O.ai Logo
6,013 views|4,112 comparisons
IBM Watson Studio Logo
4,270 views|3,271 comparisons
Most Helpful Review
Find out what your peers are saying about H2O.ai vs. IBM Watson Studio and other solutions. Updated: January 2020.
391,616 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
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.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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The system's ability to take a look at data, segment it and then use that data very differently.The scalability of IBM Watson Studio is great.The most important thing is that it's a multi-faceted solution. It's a kind of specialist, not a generalist. It can produce very specific information for the customer. It's totally different from Google or any search engine that produces generic information. It's specialty is that it's all on video.The solution is very easy to use.It is a stable, reliable product.Technical support is great. We have had weekly teleconferences with the technical people at IBM, and they have been fantastic.The main benefit is the ease of use. We see a lot of engineers in our site and customers that really like the way the tools are able to work with the people.It has greatly improved the performance because it is standardized across the company.

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Cons
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.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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It's sometimes easy to get lost given the number of images the solution opens up when you click on the mouse and the amount of different tabs.The decision making in their decision making feature is less good than other options.So a better user interface could be very helpfulMore features in data virtualization would be helpful. The solution could use an interactive dashboard that could make exploration easier.We would like to see it more web-based with more functionality.We would like to see it less as one big, massive product, but more based on smaller services that we can then roll out to consumers.Initially, it was quite complex. For us, it was not only a matter of getting it installed, that was just a start. It was also trying to come up with a standard way of implementing it across the entire organization, which had been a challenge.

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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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391,616 professionals have used our research since 2012.
Ranking
10th
Views
6,013
Comparisons
4,112
Reviews
7
Average Words per Review
320
Avg. Rating
7.6
9th
Views
4,270
Comparisons
3,271
Reviews
5
Average Words per Review
456
Avg. Rating
8.2
Top Comparisons
Compared 24% of the time.
Also Known As
Watson Studio, IBM Data Science Experience, Data Science Experience, DSx
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H2O.ai
IBM
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.

IBM Watson Studio provides tools for data scientists, application developers and subject matter experts to collaboratively and easily work with data to build and train models at scale. It gives you the flexibility to build models where your data resides and deploy anywhere in a hybrid environment so you can operationalize data science faster.

Offer
Learn more about H2O.ai
Learn more about IBM Watson Studio
Sample Customers
poder.io, Stanley Black & Decker, G5, PWC, Comcast, CiscoGroupM, Accenture, Fifth Third Bank
Top Industries
VISITORS READING REVIEWS
Software R&D Company38%
Comms Service Provider16%
Transportation Company9%
Financial Services Firm8%
VISITORS READING REVIEWS
Software R&D Company39%
Comms Service Provider11%
Retailer9%
Media Company5%
Find out what your peers are saying about H2O.ai vs. IBM Watson Studio and other solutions. Updated: January 2020.
391,616 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.