TrustRadius

Domino Enterprise MLOps Platform vs. IBM Watson Studio on Cloud Pak for Data

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Domino Enterprise MLOps Platform
Score 8.0 out of 10
Enterprise companies (1,001+ employees)
The Domino Enterprise MLOps Platform helps data science teams improve the speed, quality and impact of data science at scale. Domino is presented as open and flexible, to empower professional data scientists to use their preferred tools and infrastructure. Data science models get into production fast and are kept operating at peak performance with integrated workflows. Domino also delivers the security, governance and compliance that enterprises expect. The Domino Enterprise MLOps…N/A
IBM Watson Studio
Score 9.1 out of 10
N/A
IBM Watson Studio enables users to build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio enables users can operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. The vendor states the solution simplifies AI lifecycle management and accelerates time to value with an open, flexible multicloud architecture.N/A
Pricing
Domino Enterprise MLOps PlatformIBM Watson Studio on Cloud Pak for Data
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Domino Enterprise MLOps PlatformIBM Watson Studio
Free Trial
YesNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
Community Pulse
Domino Enterprise MLOps PlatformIBM Watson Studio on Cloud Pak for Data
Top Pros

No answers on this topic

Top Cons

No answers on this topic

Features
Domino Enterprise MLOps PlatformIBM Watson Studio on Cloud Pak for Data
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Domino Enterprise MLOps Platform
-
Ratings
IBM Watson Studio on Cloud Pak for Data
8.1
22 Ratings
4% below category average
Connect to Multiple Data Sources00 Ratings8.022 Ratings
Extend Existing Data Sources00 Ratings8.022 Ratings
Automatic Data Format Detection00 Ratings10.021 Ratings
MDM Integration00 Ratings6.414 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Domino Enterprise MLOps Platform
-
Ratings
IBM Watson Studio on Cloud Pak for Data
10.0
22 Ratings
17% above category average
Visualization00 Ratings10.022 Ratings
Interactive Data Analysis00 Ratings10.022 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Domino Enterprise MLOps Platform
-
Ratings
IBM Watson Studio on Cloud Pak for Data
9.5
22 Ratings
14% above category average
Interactive Data Cleaning and Enrichment00 Ratings10.022 Ratings
Data Transformations00 Ratings10.021 Ratings
Data Encryption00 Ratings8.020 Ratings
Built-in Processors00 Ratings10.021 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Domino Enterprise MLOps Platform
-
Ratings
IBM Watson Studio on Cloud Pak for Data
9.5
22 Ratings
11% above category average
Multiple Model Development Languages and Tools00 Ratings10.021 Ratings
Automated Machine Learning00 Ratings10.022 Ratings
Single platform for multiple model development00 Ratings10.022 Ratings
Self-Service Model Delivery00 Ratings8.020 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Domino Enterprise MLOps Platform
-
Ratings
IBM Watson Studio on Cloud Pak for Data
8.0
22 Ratings
7% below category average
Flexible Model Publishing Options00 Ratings9.022 Ratings
Security, Governance, and Cost Controls00 Ratings7.022 Ratings
Best Alternatives
Domino Enterprise MLOps PlatformIBM Watson Studio on Cloud Pak for Data
Small Businesses
IBM SPSS Modeler
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Score 7.8 out of 10
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Score 7.8 out of 10
Medium-sized Companies
Mathematica
Mathematica
Score 8.2 out of 10
Mathematica
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Score 8.2 out of 10
Enterprises
IBM SPSS Modeler
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Score 7.8 out of 10
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Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Domino Enterprise MLOps PlatformIBM Watson Studio on Cloud Pak for Data
Likelihood to Recommend
-
(0 ratings)
8.0
(65 ratings)
Likelihood to Renew
-
(0 ratings)
8.2
(1 ratings)
Usability
-
(0 ratings)
9.6
(2 ratings)
Availability
-
(0 ratings)
8.2
(1 ratings)
Performance
-
(0 ratings)
8.2
(1 ratings)
Support Rating
-
(0 ratings)
8.2
(1 ratings)
In-Person Training
-
(0 ratings)
8.2
(1 ratings)
Online Training
-
(0 ratings)
8.2
(1 ratings)
Implementation Rating
-
(0 ratings)
7.3
(1 ratings)
Product Scalability
-
(0 ratings)
8.2
(1 ratings)
Vendor post-sale
-
(0 ratings)
7.3
(1 ratings)
Vendor pre-sale
-
(0 ratings)
8.2
(1 ratings)
User Testimonials
Domino Enterprise MLOps PlatformIBM Watson Studio on Cloud Pak for Data
Likelihood to Recommend
Domino Data Lab
No answers on this topic
IBM
It has a lot of features that are good for teams working on large-scale projects and continuously developing and reiterating their data project models. Really helpful when dealing with large data. It is a kind of one-stop solution for all data science tasks like visualization, cleaning, analyzing data, and developing models but small teams might find a lot of features unuseful.
Verified User
Anonymous
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Pros
Domino Data Lab
No answers on this topic
IBM
  • Integration of IBM Watson APIs such as speech to text, image recognition, personality insights, etc.
  • SPSS modeler and neural network model provide no-code environments for data scientists to build pipelines quickly.
  • Enforced best-practices set up POCs for deployment in production with a minimum of re-work.
  • Estimator validation lets data scientists test and prove different models.
Christopher Penn | TrustRadius Reviewer
Christopher Penn
Co-Founder and Chief Innovator
Read full review
Cons
Domino Data Lab
No answers on this topic
IBM
  • The cost is steep and so only companies with resources can afford it
  • It will be nice to have Chinese versions so that Chinese engineers can also use it easily
  • It takes a while to learn how to input different kinds of skin defects for detection
Verified User
Anonymous
Read full review
Likelihood to Renew
Domino Data Lab
No answers on this topic
IBM
because we find out that DSX results have improved our approach to the whole subject (data, models, procedures)
Davide Tognon | TrustRadius Reviewer
Davide Tognon
Engineering Technician
Read full review
Usability
Domino Data Lab
No answers on this topic
IBM
The UI flawlessly merges this offering by providing a neat, minimal, responsive interface
Isaiah King | TrustRadius Reviewer
Isaiah King
Founding Member
Read full review
Reliability and Availability
Domino Data Lab
No answers on this topic
IBM
From time to time there are services unavailable, but we have been always informed before and they got back to work sooner than expected
Davide Tognon | TrustRadius Reviewer
Davide Tognon
Engineering Technician
Read full review
Performance
Domino Data Lab
No answers on this topic
IBM
Never had slow response even on our very busy network
Davide Tognon | TrustRadius Reviewer
Davide Tognon
Engineering Technician
Read full review
Support Rating
Domino Data Lab
No answers on this topic
IBM
I received answers mostly at once and got answered even further my question: they gave me interesting points of view and suggestion for deepening in the learning path
Davide Tognon | TrustRadius Reviewer
Davide Tognon
Engineering Technician
Read full review
In-Person Training
Domino Data Lab
No answers on this topic
IBM
The trainers on the job are very smart with solutions and very able in teaching
Davide Tognon | TrustRadius Reviewer
Davide Tognon
Engineering Technician
Read full review
Online Training
Domino Data Lab
No answers on this topic
IBM
The Platform is very handy and suggests further steps according my previous interests
Davide Tognon | TrustRadius Reviewer
Davide Tognon
Engineering Technician
Read full review
Implementation Rating
Domino Data Lab
No answers on this topic
IBM
It surprised us with unpredictable case of use and brand new points of view
Davide Tognon | TrustRadius Reviewer
Davide Tognon
Engineering Technician
Read full review
Alternatives Considered
Domino Data Lab
No answers on this topic
IBM
The main reason I personally changed over from Azure ML Studio is because it lacked any support for significant custom modelling with packages and services such as TensorFlow, scikit-learn, Microsoft Cognitive Toolkit and Spark ML. IBM Watson Studio provides these services and does so in a well integrated and easy to use fashion making it a preferable service over the other services that I have personally used.
Verified User
Anonymous
Read full review
Scalability
Domino Data Lab
No answers on this topic
IBM
It helped us in getting from 0 to DSX without getting lost
Davide Tognon | TrustRadius Reviewer
Davide Tognon
Engineering Technician
Read full review
Return on Investment
Domino Data Lab
No answers on this topic
IBM
  • Could instantly show data driven insights to drive 20% incremental revenue over existing results
  • Still don't have a real use case for unstructured data like twitter feed
  • Some of the insights around user actions have driven new projects to automate mundane tasks
Verified User
Anonymous
Read full review
ScreenShots

Domino Enterprise MLOps Platform Screenshots

Screenshot of The Domino Enterprise MLOps Platform helps data science teams improve the speed, quality and impact of data science at scale.Screenshot of The Self-Service Infrastructure Portal makes data science teams more productive with access to their preferred tools, scalable compute, and diverse data sets. By automating time-consuming DevOps tasks, data scientists can focus on the tasks at hand.Screenshot of The Integrated Model Factory includes a workbench, model and app deployment, and integrated monitoring to rapidly experiment, deploy the best models in production, ensure optimal performance, and collaborate across the end-to-end data science lifecycle.Screenshot of The System of Record has a reproducibility engine, search and knowledge management, and integrated project management. Teams can find, reuse, reproduce, and build on any data science work to amplify innovation.Screenshot of Model monitoring capabilities ensure that all production models maintain peak performance. Automated alerts provide notification when data and quality drift occurs so users can re-train, rebuild, and re-publish the model.Screenshot of Nexus is a single pane of glass to run data science and ML workloads across any compute cluster — in any cloud, region, or on-premises. It unifies data science silos across the enterprise, providing one place to build, deploy, and monitor models.