DataRobot vs. IBM Watson Studio on Cloud Pak for Data

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
DataRobot
Score 8.9 out of 10
N/A
The DataRobot AI Platform is presented as a solution that accelerates and democratizes data science by automating the end-to-end journey from data to value and allows users to deploy AI applications at scale. DataRobot provides a centrally governed platform that gives users AI to drive business outcomes, that is available on the user's cloud platform-of-choice, on-premise, or as a fully-managed service. The solutions include tools providing data preparation enabling users to explore and…
$0
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
DataRobotIBM Watson Studio on Cloud Pak for Data
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
DataRobotIBM Watson Studio
Free Trial
YesNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
YesNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
DataRobotIBM Watson Studio on Cloud Pak for Data
Considered Both Products
DataRobot

No answer on this topic

IBM Watson Studio
Chose IBM Watson Studio on Cloud Pak for Data
AWS stacks up very favourably against Watson Studio, and in fact this is what the customer ultimately chose over Watson Studio after an evaluation period due to the sophistication, maturity, security, and capabilities of the AWS components. The downsides of AWS are having to …
Top Pros
Top Cons
Features
DataRobotIBM Watson Studio on Cloud Pak for Data
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
DataRobot
7.1
54 Ratings
17% below category average
IBM Watson Studio on Cloud Pak for Data
8.1
22 Ratings
4% below category average
Connect to Multiple Data Sources6.149 Ratings8.022 Ratings
Extend Existing Data Sources5.844 Ratings8.022 Ratings
Automatic Data Format Detection8.452 Ratings10.021 Ratings
MDM Integration8.024 Ratings6.414 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
DataRobot
7.9
53 Ratings
7% below category average
IBM Watson Studio on Cloud Pak for Data
10.0
22 Ratings
17% above category average
Visualization8.052 Ratings10.022 Ratings
Interactive Data Analysis7.851 Ratings10.022 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
DataRobot
7.7
52 Ratings
7% below category average
IBM Watson Studio on Cloud Pak for Data
9.5
22 Ratings
14% above category average
Interactive Data Cleaning and Enrichment7.445 Ratings10.022 Ratings
Data Transformations7.550 Ratings10.021 Ratings
Data Encryption8.126 Ratings8.020 Ratings
Built-in Processors7.942 Ratings10.021 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
DataRobot
8.6
55 Ratings
1% above category average
IBM Watson Studio on Cloud Pak for Data
9.5
22 Ratings
11% above category average
Multiple Model Development Languages and Tools7.746 Ratings10.021 Ratings
Automated Machine Learning9.355 Ratings10.022 Ratings
Single platform for multiple model development9.052 Ratings10.022 Ratings
Self-Service Model Delivery8.451 Ratings8.020 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
DataRobot
8.3
49 Ratings
3% below category average
IBM Watson Studio on Cloud Pak for Data
8.0
22 Ratings
7% below category average
Flexible Model Publishing Options8.449 Ratings9.022 Ratings
Security, Governance, and Cost Controls8.243 Ratings7.022 Ratings
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DataRobotIBM Watson Studio on Cloud Pak for Data
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Score 8.2 out of 10
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User Ratings
DataRobotIBM Watson Studio on Cloud Pak for Data
Likelihood to Recommend
8.2
(59 ratings)
8.0
(65 ratings)
Likelihood to Renew
6.4
(4 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
8.2
(5 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
DataRobotIBM Watson Studio on Cloud Pak for Data
Likelihood to Recommend
DataRobot
DataRobot can be used for risk assessment, such as predicting the likelihood of loan default. It can handle both classification and regression tasks effectively. It relies on historical data for model training. If you have limited historical data or the data quality is poor, it may not be the best choice as it requires a sufficient amount of high-quality data for accurate model building.
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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
DataRobot
  • DataRobot helps, with algorithms, to analyze and decipher numerous machine-learning techniques in order to provide models to assist in company-wide decision making.
  • Our DataRobot program puts on an "even playing field" the strength of auto-machine learning and allows us to make decisions in an extremely timely manner. The speed is consistent without being offset by errors or false-negatives.
  • It encompasses many desired techniques that help companies in general, to reconfigure in to artificial intelligence driven firms, with little to no inconvenience.
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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.
Read full review
Cons
DataRobot
  • The platform itself is very complicated. It probably can't function well without being complicated, but there is a big training curve to get over before you can effectively use it. Even I'm not sure if I'm effectively using it now.
  • The suggested model DataRobot deploys often not the best model for our purposes. We've had to do a lot of testing to make sure what model is the best. For regressive models, DataRobot does give you a MASE score but, for some reason, often doesn't suggest the best MASE score model.
  • The software will give you errors if output files are not entered correctly but will not exactly tell you how to fix them. Perhaps that is complicated, but being able to download a template with your data for an output file in the correct format would be nice.
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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
DataRobot
DataRobot presents a machine-learning platform designed by data scientists from an array of backgrounds, to construct and develop precise predictive modeling in a fraction of the time previously taken. The tech invloved addresses the critical shortage of data scientists by changing the speed and economics of predictive analytics. DataRobot utilizes parallel processing to evaluate models in R, Python, Spark MLlib, H2O and other open source databases. It searches for possible permutations and algorithms, features, transformation, processes, steps and tuning to yield the best models for the dataset and predictive goal.
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IBM
because we find out that DSX results have improved our approach to the whole subject (data, models, procedures)
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Usability
DataRobot
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
DataRobot
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
DataRobot
No answers on this topic
IBM
Never had slow response even on our very busy network
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Support Rating
DataRobot
As I am writing this report I am participating with Datarobot Engineers in an complex environment and we have their whole support. We are in Mexico and is not common to have this commitment from companies without expensive contract services. Installing is on premise and the client does not want us to take control and they, the client, is also limited because of internal IT regulations ,,, soo we are just doing magic and everybody is committed.
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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
DataRobot
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
DataRobot
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
DataRobot
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
DataRobot
I've done machine learning through python before, however having to code and test each model individually was very time consuming and required a lot of expertise. The data Robot approach, is an excellent way of getting to a well placed starting point. You can then pick up the model from there and fine tune further if you need.
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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
DataRobot
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
DataRobot
  • We have been able to cut costs by not buying leads that we will not be able to sell on
  • We have been able to deploy loan eligibility reporting which brought in new business
  • We have been able to improve the performance of our credit providers and our partners which has helped to retain business
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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
Read full review
ScreenShots

DataRobot Screenshots

Screenshot of Decision FlowsScreenshot of No Code App BuilderScreenshot of AI AppsScreenshot of Automated Time SeriesScreenshot of MLOpsScreenshot of Model Insights