Cloudera Data Platform vs. IBM Watson Studio on Cloud Pak for Data

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Cloudera Data Platform
Score 6.5 out of 10
N/A
Cloudera Data Platform (CDP), launched September 2019, is designed to combine the best of Hortonworks and Cloudera technologies to deliver an enterprise data cloud. CDP includes the Cloudera Data Warehouse and machine learning services as well as a Data Hub service for building custom business applications.
$0.04
per CCU (hourly rate)
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
Cloudera Data PlatformIBM Watson Studio on Cloud Pak for Data
Editions & Modules
CDP Public Cloud - Data Hub
$0.04
per CCU (hourly rate)
CDP Public Cloud - Data Warehouse
$0.054
per CCU (hourly rate)
CDP Public Cloud - Data Engineering
$0.07
per CCU (hourly rate)
CDP Public Cloud - Operational Database
$0.08
per CCU (hourly rate)
CDP Public Cloud - Flow Management
$0.15
per CCU (hourly rate)
CDP Public Cloud - Machine Learning
$0.17
per CCU (hourly rate)
CDP Private Cloud - Plus Edition
$400
CCU (annual subscription)
CDP Private Cloud - Base Edition
$10,000.00
node + variable (annual subscription)
No answers on this topic
Offerings
Pricing Offerings
Cloudera Data PlatformIBM Watson Studio
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Cloudera Data PlatformIBM Watson Studio on Cloud Pak for Data
Top Pros
Top Cons
Features
Cloudera Data PlatformIBM Watson Studio on Cloud Pak for Data
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Cloudera Data 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
Cloudera Data 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
Cloudera Data 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
Cloudera Data 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
Cloudera Data 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
Cloudera Data PlatformIBM Watson Studio on Cloud Pak for Data
Small Businesses
Google BigQuery
Google BigQuery
Score 8.6 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Medium-sized Companies
Cloudera Enterprise Data Hub
Cloudera Enterprise Data Hub
Score 9.0 out of 10
Mathematica
Mathematica
Score 8.3 out of 10
Enterprises
Oracle Exadata
Oracle Exadata
Score 8.2 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Cloudera Data PlatformIBM Watson Studio on Cloud Pak for Data
Likelihood to Recommend
7.0
(1 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
8.0
(1 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
Cloudera Data PlatformIBM Watson Studio on Cloud Pak for Data
Likelihood to Recommend
Cloudera
I have seen that Cloudera Data Platform is well suited for large batch processes. It works really well for our indication analyses that are performed by the actuaries. I feel that rapid streaming operations may be a situation where additional technology would be needed to provide for a robust solution.
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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.
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Pros
Cloudera
  • Scales
  • Highly available
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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.
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Cons
Cloudera
  • Constantly changing costs
  • Log visibility
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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
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Likelihood to Renew
Cloudera
No answers on this topic
IBM
because we find out that DSX results have improved our approach to the whole subject (data, models, procedures)
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Usability
Cloudera
No answers on this topic
IBM
The UI flawlessly merges this offering by providing a neat, minimal, responsive interface
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Reliability and Availability
Cloudera
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
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Performance
Cloudera
No answers on this topic
IBM
Never had slow response even on our very busy network
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Support Rating
Cloudera
We have utilized Cloudera support quite frequently and are very satisfied with the capability and responsiveness of that team. Often, the new features delivered with the platform give us an opportunity to mature the way we're doing things, and the support team have been valuable in developing those new patterns.
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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
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In-Person Training
Cloudera
No answers on this topic
IBM
The trainers on the job are very smart with solutions and very able in teaching
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Online Training
Cloudera
No answers on this topic
IBM
The Platform is very handy and suggests further steps according my previous interests
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Implementation Rating
Cloudera
No answers on this topic
IBM
It surprised us with unpredictable case of use and brand new points of view
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Alternatives Considered
Cloudera
IBM's offering of the Cloud Pak for Data has been a moving target and difficult to compare to Cloudera Data Platform. We have implemented our solution on Amazon Web Services, which appears to be supported by IBM at this point, but the migration would be very expensive for us to endeavor.
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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.
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Scalability
Cloudera
No answers on this topic
IBM
It helped us in getting from 0 to DSX without getting lost
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Return on Investment
Cloudera
  • Reduced operational costs
  • Speed to market
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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
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ScreenShots