Domino Data Science Platform vs IBM Watson Studio comparison

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Domino Data Lab Logo
2,713 views|2,334 comparisons
100% willing to recommend
IBM Logo
3,410 views|2,249 comparisons
100% willing to recommend
Comparison Buyer's Guide
Executive Summary

We performed a comparison between Domino Data Science Platform and IBM Watson Studio 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: April 2024).
768,415 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 scalability of the solution is good; I'd rate it four out of five."

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"The scalability of IBM Watson Studio is great.""IBM Watson Studio consistently automates across channels.""It is a very stable and reliable solution.""For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks.""The system's ability to take a look at data, segment it and then use that data very differently.""Watson Studio is very stable.""It has greatly improved the performance because it is standardized across the company.""It has a lot of data connectors, which is extremely helpful."

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Cons
"The predictive analysis feature needs improvement."

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"I want IBM's technical support team to provide more specific answers to queries.""The solution's interface is very slow at times.""Watson Studio would be improved with a clearer path for the deployment of docker images.""I think maybe the support is an area where it lacks.""Some of the solutions are really good solutions but they can be a little too costly for many.""The decision making in their decision making feature is less good than other options.""We would like to see it more web-based with more functionality.""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."

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Pricing and Cost Advice
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  • "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."
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    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
    18th
    Views
    2,713
    Comparisons
    2,334
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    11th
    Views
    3,410
    Comparisons
    2,249
    Reviews
    5
    Average Words per Review
    426
    Rating
    8.2
    Comparisons
    Also Known As
    Domino Data Lab Platform
    Watson Studio, IBM Data Science Experience, Data Science Experience, DSx
    Learn More
    Domino Data Lab
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    IBM
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    Overview

    Domino provides a central system of record that keeps track of all data science activity across an organization. Domino helps data scientists seamlessly orchestrate AWS hardware and software toolkits, increase flexibility and innovation, and maintain required IT controls and standards. Organizations can automatically keep track of all data, tools, experiments, results, discussion, and models, as well as dramatically scale data science investments and impact decision-making across divisions. The platform helps organizations work faster, deploy results sooner, scale rapidly, and reduce regulatory and operational risk.

    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
    Allstate, Tesla, Dell, Moody's Analytics, SurveyMonkey, Eventbrite, Carnival
    GroupM, Accenture, Fifth Third Bank
    Top Industries
    VISITORS READING REVIEWS
    Financial Services Firm29%
    Insurance Company11%
    Manufacturing Company10%
    Computer Software Company8%
    REVIEWERS
    Manufacturing Company22%
    Insurance Company11%
    Marketing Services Firm11%
    Comms Service Provider11%
    VISITORS READING REVIEWS
    Financial Services Firm16%
    Computer Software Company11%
    Comms Service Provider8%
    Educational Organization7%
    Company Size
    VISITORS READING REVIEWS
    Small Business9%
    Midsize Enterprise7%
    Large Enterprise85%
    REVIEWERS
    Small Business71%
    Large Enterprise29%
    VISITORS READING REVIEWS
    Small Business21%
    Midsize Enterprise12%
    Large Enterprise67%
    Buyer's Guide
    Data Science Platforms
    April 2024
    Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms. Updated: April 2024.
    768,415 professionals have used our research since 2012.

    Domino Data Science Platform is ranked 18th in Data Science Platforms while IBM Watson Studio is ranked 11th in Data Science Platforms with 13 reviews. Domino Data Science Platform is rated 7.0, while IBM Watson Studio is rated 8.2. The top reviewer of Domino Data Science Platform writes "Good scalability and stability but the predictive analysis feature needs improvement". 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". Domino Data Science Platform is most compared with Databricks, Amazon SageMaker, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio and Cloudera Data Science Workbench, whereas IBM Watson Studio is most compared with Databricks, Microsoft Azure Machine Learning Studio, Azure OpenAI, Google Vertex AI and Amazon Comprehend.

    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.