Compare Amazon SageMaker vs. IBM Watson Studio

Amazon SageMaker is ranked 13th in Data Science Platforms with 2 reviews while IBM Watson Studio is ranked 9th in Data Science Platforms with 6 reviews. Amazon SageMaker is rated 7.6, while IBM Watson Studio is rated 8.4. The top reviewer of Amazon SageMaker writes "A solution with great computational storage, has many pre-built models, is stable, and has good support". 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". Amazon SageMaker is most compared with Databricks, Microsoft Azure Machine Learning Studio and Cloudera Data Science Workbench, whereas IBM Watson Studio is most compared with IBM SPSS Modeler, Microsoft Azure Machine Learning Studio and Amazon SageMaker. See our Amazon SageMaker vs. IBM Watson Studio report.
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Most Helpful Review
Find out what your peers are saying about Amazon SageMaker vs. IBM Watson Studio and other solutions. Updated: January 2020.
390,232 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
They are doing a good job of evolving.The few projects we have done have been promising.

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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
I would suggest that Amazon SageMaker provide free slots to allow customers to practice, such as a free slot to try out working with a Sandbox.I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time.

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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
The pricing is complicated as it is based on what kind of machines you are using, the type of storage, and the kind of computation.

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Ranking
13th
Views
5,586
Comparisons
5,163
Reviews
2
Average Words per Review
517
Avg. Rating
7.5
9th
Views
4,270
Comparisons
3,271
Reviews
5
Average Words per Review
456
Avg. Rating
8.2
Top Comparisons
Compared 30% of the time.
Also Known As
AWS SageMaker, SageMakerWatson Studio, IBM Data Science Experience, Data Science Experience, DSx
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Amazon
IBM
Overview

Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.

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 Amazon SageMaker
Learn more about IBM Watson Studio
Sample Customers
DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, IntuitGroupM, Accenture, Fifth Third Bank
Top Industries
VISITORS READING REVIEWS
Software R&D Company34%
Media Company15%
Comms Service Provider9%
Retailer8%
VISITORS READING REVIEWS
Software R&D Company39%
Retailer11%
Comms Service Provider8%
Media Company5%
Find out what your peers are saying about Amazon SageMaker vs. IBM Watson Studio and other solutions. Updated: January 2020.
390,232 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.