Amazon SageMaker vs IBM Watson Studio comparison

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Amazon Web Services (AWS) Logo
11,426 views|9,062 comparisons
84% willing to recommend
IBM Logo
3,203 views|2,111 comparisons
100% willing to recommend
Comparison Buyer's Guide
Executive Summary

We performed a comparison between Amazon SageMaker and IBM Watson Studio based on real PeerSpot user reviews.

Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
To learn more, read our detailed Amazon SageMaker vs. IBM Watson Studio Report (Updated: May 2024).
772,567 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
"The deployment is very good, where you only need to press a few buttons.""The superb thing that SageMaker brings is that it wraps everything well. It's got the deployment, the whole framework.""The Autopilot feature is really good because it's helpful for people who don't have much experience with coding or data pipelines. When we suggest SageMaker to clients, they don't have to go through all the steps manually. They can leverage Autopilot to choose variables, run experiments, and monitor costs. The results are also pretty accurate.""We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to ChatGPT that requires models. We utilize Amazon SageMaker to create endpoints for these models, making accessing them convenient as needed.""We were able to use the product to automate processes.""The tool has made client management easier where patients need to upload their health records and we can use the tool to understand details on treatment date, amount, etc.""We've had no problems with SageMaker's stability.""I have contacted the solution's technical support, and they were really good. I rate the technical support a ten out of ten."

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"It is a very stable and reliable solution.""The solution is very easy to use.""It is a stable, reliable product.""The system's ability to take a look at data, segment it and then use that data very differently.""Stability-wise, it is a great tool.""It has a lot of data connectors, which is extremely helpful.""It has greatly improved the performance because it is standardized across the company.""The scalability of IBM Watson Studio is great."

More IBM Watson Studio Pros →

Cons
"SageMaker would be improved with the addition of reporting services.""In general, improvements are needed on the performance side of the product's graphical user interface-related area since it consumes a lot of time for a user.""The solution is complex to use.""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.""The payment and monitoring metrics are a bit confusing not only for Amazon SageMaker but also for the range of other products that fall under AWS, especially for a new user of the product.""The documentation must be made clearer and more user-friendly.""Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier.""Creating notebook instances for multiple users is pretty expensive in Amazon SageMaker."

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"More features in data virtualization would be helpful. The solution could use an interactive dashboard that could make exploration easier.""Watson Studio would be improved with a clearer path for the deployment of docker images.""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.""I want IBM's technical support team to provide more specific answers to queries.""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.""Some of the solutions are really good solutions but they can be a little too costly for many.""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."

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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."
  • "The support costs are 10% of the Amazon fees and it comes by default."
  • "SageMaker is worth the money for our use case."
  • "Databricks solution is less costly than Amazon SageMaker."
  • "I would rate the solution's price a ten out of ten since it is very high."
  • "There is no license required for the solution since you can use it on demand."
  • "I rate the pricing a five on a scale of one to ten, where one is the lowest price, and ten is the highest price. The solution is priced reasonably. There is no additional cost to be paid in excess of the standard licensing fees."
  • "You don't pay for Sagemaker. You only pay for the compute instances in your storage."
  • More Amazon SageMaker Pricing and Cost Advice →

  • "Watson Studio's pricing is reasonable for what you get."
  • "IBM Watson Studio is a reasonably priced product"
  • "IBM Watson Studio is an expensive solution."
  • "The pricing is generally reasonable and straightforward but can vary significantly depending on the specific workloads in use."
  • More IBM Watson Studio Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:We researched AWS SageMaker, but in the end, we chose Databricks Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It… more »
    Top Answer:We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to ChatGPT that requires models. We utilize Amazon SageMaker to create endpoints for… more »
    Top Answer:From an improvement perspective, I would say that if the deployment environment and IBM Watson Studio's environment are separated, then it would be good. I would like them to be one and offer users a… more »
    Ranking
    5th
    Views
    11,426
    Comparisons
    9,062
    Reviews
    11
    Average Words per Review
    536
    Rating
    7.2
    10th
    Views
    3,203
    Comparisons
    2,111
    Reviews
    5
    Average Words per Review
    426
    Rating
    8.2
    Comparisons
    Also Known As
    AWS SageMaker, SageMaker
    Watson Studio, IBM Data Science Experience, Data Science Experience, DSx
    Learn More
    IBM
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    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.

    Sample Customers
    DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit
    GroupM, Accenture, Fifth Third Bank
    Top Industries
    REVIEWERS
    Computer Software Company22%
    Manufacturing Company11%
    Logistics Company11%
    Transportation Company11%
    VISITORS READING REVIEWS
    Financial Services Firm17%
    Educational Organization13%
    Computer Software Company11%
    Manufacturing Company8%
    REVIEWERS
    Manufacturing Company22%
    Insurance Company11%
    Marketing Services Firm11%
    Comms Service Provider11%
    VISITORS READING REVIEWS
    Financial Services Firm16%
    Computer Software Company12%
    Manufacturing Company8%
    Educational Organization7%
    Company Size
    REVIEWERS
    Small Business15%
    Midsize Enterprise40%
    Large Enterprise45%
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise18%
    Large Enterprise68%
    REVIEWERS
    Small Business71%
    Large Enterprise29%
    VISITORS READING REVIEWS
    Small Business21%
    Midsize Enterprise13%
    Large Enterprise66%
    Buyer's Guide
    Amazon SageMaker vs. IBM Watson Studio
    May 2024
    Find out what your peers are saying about Amazon SageMaker vs. IBM Watson Studio and other solutions. Updated: May 2024.
    772,567 professionals have used our research since 2012.

    Amazon SageMaker is ranked 5th in Data Science Platforms with 19 reviews while IBM Watson Studio is ranked 10th in Data Science Platforms with 13 reviews. Amazon SageMaker is rated 7.4, while IBM Watson Studio is rated 8.2. The top reviewer of Amazon SageMaker writes "Easy to use and manage, but the documentation does not have a lot of information". On the other hand, the top reviewer of IBM Watson Studio writes "A highly robust and well-documented platform that simplifies the complex world of AI". Amazon SageMaker is most compared with Databricks, Azure OpenAI, Google Vertex AI, Domino Data Science Platform and Microsoft Azure Machine Learning Studio, whereas IBM Watson Studio is most compared with Databricks, Azure OpenAI, Microsoft Azure Machine Learning Studio, Google Vertex AI and Amazon Comprehend. See our Amazon SageMaker vs. IBM Watson Studio report.

    See our list of best Data Science Platforms vendors and best AI Development 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.