Cloudera Data Science Workbench vs. DataRobot

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Data Science Workbench
Score 6.7 out of 10
N/A
Cloudera Data Science Workbench enables secure self-service data science for the enterprise. It is a collaborative environment where developers can work with a variety of libraries and frameworks.N/A
DataRobot
Score 8.2 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…N/A
Pricing
Cloudera Data Science WorkbenchDataRobot
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Data Science WorkbenchDataRobot
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Cloudera Data Science WorkbenchDataRobot
Considered Both Products
Data Science Workbench
Chose Data Science Workbench
Since our organization had already implemented Cloudera Data Platform as our Big Data Warehouse platform, implementing CDSW as the go-to Analytic and Data Science Platform is the most logical and cost-effective decision to make. It integrates seamlessly with our CDH clusters …
Chose Data Science Workbench
Both the tools have similar features and have made it pretty easy to install/deploy/use. Depending on your existing platform (Cloudera vs. Azure) you need to pick the Workbench. Another observation is that Cloudera has better support where you can get feedback on your questions …
DataRobot
Chose DataRobot
DataRobot is more friction-less and comprehensive enough to tackle a majority of our use cases.
Chose 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 …
Chose DataRobot
DataRobot outperforms SPSS in terms of speed and efficiency. While I continue to rely on SPSS for tasks like data cleanup and data engineering, I have noticed that DataRobot significantly excels when it comes to building models. Its speed and user-friendly interface make it the …
Chose DataRobot
Comparable to H2O but my company chose DataRobot so that's why I'm using it. Pricing is reasonable and the feature coverage is probably better from an end-to-end perspective. DataRobot has less flexibility than Amazon SageMaker but is a lot simpler to use, which again for a …
Chose DataRobot
Alteryx is more of data processing only with user-friendly interface for non-technical users. Data Robot is more than that and can provide intelligent models for machine learning.
Chose DataRobot
Better user interface and collaborative capabilities to enable easy explanation among business partners with the platforms insightful visualizations.
Chose DataRobot
I have not used any comparable products. Compared to using commonly available open source libraries for machine learning, DataRobot automatically manages the partition of data, pre-processing of data, construction of processing pipelines and the evaluation of models on an …
Chose DataRobot
Robots vs. Robots. It was necessarily me who selected DR instead, but having used both, I find that DR is better suited to our needs and is just more accessible. You don't need to be a complete expert in the field to be able to use DR's platform, more just being able to …
Chose DataRobot
When we ran the purchase process, two factors were critical: price of course and the customer success service as we were new in this datascience world. H2O and DataRobot were the finalists (Dataiku too expensive for our needs), but we decide to choose DataRobot as they give us …
Chose DataRobot
DataRobot provided the perfect balance of features and price points. The other tools we tried were very expensive and provided extra things that we really didn't need. Some of the other tools also required you to host them on a server at your institution or pay for their cloud …
Chose DataRobot
We consistently return to DataRobot for its ease of use and ability to get the job done without major hurdles. Thus far, we just haven't found that in other products.
H2O.ai (Driverless AI): several test models did not complete, and H2O.ai team could not explain why.
Sagemaker:…
Chose DataRobot
At the time DataRobot provided a more automatized and complete variety of pre-trained models and ready-to-use solutions.
Chose DataRobot
We've just had an intro but DataRobot is much more specialized in predictive analytics. Dataiku seems for me a platform that aims to cover a little bit all the steps or processes of a D&A team and with this approach, you may be doing a trade-off in quality and power
Chose DataRobot
The ease of use has been one significant factor and productionizing is the second one that stands out. Comparision across various models
Chose DataRobot
DataRobot is the product that seemed to have the most professional platform all in all. It was also the best one for the second part of the model development, which is monitoring what the model is doing in production and governing what that model was doing, giving us the …
Chose DataRobot
Amazon SageMaker and Python IDLE
Chose DataRobot
DataRobot is far easier to implement and much easier to master. The license cost considerations are more economically favorable also.
Features
Cloudera Data Science WorkbenchDataRobot
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Cloudera Data Science Workbench
7.5
Ratings
11% below category average
DataRobot
-
Ratings
Connect to Multiple Data Sources7.00 Ratings00 Ratings
Extend Existing Data Sources8.00 Ratings00 Ratings
Automatic Data Format Detection7.00 Ratings00 Ratings
MDM Integration8.00 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Cloudera Data Science Workbench
7.6
Ratings
10% below category average
DataRobot
-
Ratings
Visualization7.10 Ratings00 Ratings
Interactive Data Analysis8.00 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Cloudera Data Science Workbench
7.8
Ratings
4% below category average
DataRobot
-
Ratings
Interactive Data Cleaning and Enrichment7.00 Ratings00 Ratings
Data Transformations8.00 Ratings00 Ratings
Data Encryption8.00 Ratings00 Ratings
Built-in Processors8.00 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Cloudera Data Science Workbench
7.6
Ratings
10% below category average
DataRobot
-
Ratings
Multiple Model Development Languages and Tools8.00 Ratings00 Ratings
Automated Machine Learning7.00 Ratings00 Ratings
Single platform for multiple model development7.10 Ratings00 Ratings
Self-Service Model Delivery8.10 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Cloudera Data Science Workbench
8.0
Ratings
6% below category average
DataRobot
-
Ratings
Flexible Model Publishing Options8.10 Ratings00 Ratings
Security, Governance, and Cost Controls7.80 Ratings00 Ratings
Best Alternatives
Cloudera Data Science WorkbenchDataRobot
Small Businesses
Jupyter Notebook
Jupyter Notebook
Score 9.4 out of 10
InterSystems IRIS
InterSystems IRIS
Score 7.7 out of 10
Medium-sized Companies
Posit
Posit
Score 10.0 out of 10
InterSystems IRIS
InterSystems IRIS
Score 7.7 out of 10
Enterprises
Posit
Posit
Score 10.0 out of 10
InterSystems IRIS
InterSystems IRIS
Score 7.7 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Cloudera Data Science WorkbenchDataRobot
Likelihood to Recommend
9.0
(0 ratings)
8.6
(0 ratings)
Likelihood to Renew
-
(0 ratings)
6.3
(0 ratings)
Support Rating
7.9
(0 ratings)
8.2
(0 ratings)
User Testimonials
Cloudera Data Science WorkbenchDataRobot
Likelihood to Recommend
  • If you already have a Cloudera partnership and a cluster, having this is a no brainer.
  • It integrates well with your existing ecosystem and it immediately starts working on projects, accessing full datasets and share analysis and results.
  • With the inclusion of Kubernetes, CPU and memory across worker nodes can be managed effectively.
Read full review
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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Pros
  • Enterprise grade security.
  • Self-service analytics platform.
  • Popular programming support.
Read full review
  • The breadth of models available to use is helpful and allows much more analytical power than programming them all yourself.
  • The built-in variable diagnostics are helpful when testing large variable sets to see which perform the best.
  • Many of the adjustments on the models are easy to use/it's easy to re-run and kick off new models as you want to try new things.
Read full review
Cons
  • Not as great as RStudio; lacks some features when compared with it
  • It is quite simple still (because its very early in its initiative), and companies may want to wait until they see a more developed product
Read full review
  • Further improvements to their text analysis tool, to be more like the Qualtrics text analysis tool, would be a great addition. Qualtrics has templates built into their text analysis tool for customer service, quality control, etc, and will automatically slot your text responses into categories associated with certain sub areas of those larger categories.
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Likelihood to Renew
No answers on this topic
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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Support Rating
It is expensive and difficult to install and maintain.
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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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Alternatives Considered
Since our organization had already implemented Cloudera Data Platform as our Big Data Warehouse platform, implementing CDSW as the go-to Analytic and Data Science Platform is the most logical and cost-effective decision to make. It integrates seamlessly with our CDH clusters and it also provides enterprise-grade security for on-premise implementation.
Read full review
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.
Read full review
Return on Investment
  • Paid off for demonstration purposes.
Read full review
  • 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
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