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Cloudera Data Science Workbench vs. Domino Enterprise MLOps Platform

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
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
Pricing
Cloudera Data Science WorkbenchDomino Enterprise MLOps Platform
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Data Science WorkbenchDomino Enterprise MLOps Platform
Free Trial
NoYes
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 Science WorkbenchDomino Enterprise MLOps Platform
Top Pros

No answers on this topic

Top Cons

No answers on this topic

Features
Cloudera Data Science WorkbenchDomino Enterprise MLOps Platform
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Cloudera Data Science Workbench
7.5
2 Ratings
12% below category average
Domino Enterprise MLOps Platform
-
Ratings
Connect to Multiple Data Sources7.02 Ratings00 Ratings
Extend Existing Data Sources8.02 Ratings00 Ratings
Automatic Data Format Detection7.02 Ratings00 Ratings
MDM Integration8.02 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Cloudera Data Science Workbench
7.6
2 Ratings
10% below category average
Domino Enterprise MLOps Platform
-
Ratings
Visualization7.12 Ratings00 Ratings
Interactive Data Analysis8.02 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Cloudera Data Science Workbench
7.8
2 Ratings
6% below category average
Domino Enterprise MLOps Platform
-
Ratings
Interactive Data Cleaning and Enrichment7.02 Ratings00 Ratings
Data Transformations8.02 Ratings00 Ratings
Data Encryption8.02 Ratings00 Ratings
Built-in Processors8.02 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Cloudera Data Science Workbench
7.6
2 Ratings
11% below category average
Domino Enterprise MLOps Platform
-
Ratings
Multiple Model Development Languages and Tools8.02 Ratings00 Ratings
Automated Machine Learning7.01 Ratings00 Ratings
Single platform for multiple model development7.12 Ratings00 Ratings
Self-Service Model Delivery8.12 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Cloudera Data Science Workbench
8.0
2 Ratings
7% below category average
Domino Enterprise MLOps Platform
-
Ratings
Flexible Model Publishing Options8.12 Ratings00 Ratings
Security, Governance, and Cost Controls7.82 Ratings00 Ratings
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Cloudera Data Science WorkbenchDomino Enterprise MLOps Platform
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Medium-sized Companies
Mathematica
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Score 8.2 out of 10
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Score 8.2 out of 10
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User Ratings
Cloudera Data Science WorkbenchDomino Enterprise MLOps Platform
Likelihood to Recommend
9.0
(3 ratings)
-
(0 ratings)
Support Rating
7.9
(2 ratings)
-
(0 ratings)
User Testimonials
Cloudera Data Science WorkbenchDomino Enterprise MLOps Platform
Likelihood to Recommend
Cloudera
Organizations which already implemented on-premise Hadoop based Cloudera Data Platform (CDH) for their Big Data warehouse architecture will definitely get more value from seamless integration of Cloudera Data Science Workbench (CDSW) with their existing CDH Platform. However, for organizations with hybrid (cloud and on-premise) data platform without prior implementation of CDH, implementing CDSW can be a challenge technically and financially.
Verified User
Anonymous
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Domino Data Lab
No answers on this topic
Pros
Cloudera
  • One single IDE (browser based application) that makes Scala, R, Python integrated under one tool
  • For larger organizations/teams, it lets you be self reliant
  • As it sits on your cluster, it has very easy access of all the data on the HDFS
  • Linking with Github is a very good way to keep the code versions intact
Bharadwaj (Brad) Chivukula | TrustRadius Reviewer
Bharadwaj (Brad) Chivukula
Sr.Technical Manager/Delivery Manager
Read full review
Domino Data Lab
No answers on this topic
Cons
Cloudera
  • Installation is difficult.
  • Upgrades are difficult.
  • Licensing options are not flexible.
Verified User
Anonymous
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Domino Data Lab
No answers on this topic
Support Rating
Cloudera
Cloudera Data Science Workbench has excellence online resources support such as documentation and examples. On top of that the enterprise license also comes with SLA on opening a ticket to Cloudera Services and support for complaint handling and troubleshooting by email or through a phone call. On top of that it also offers additional paid training services.
Verified User
Anonymous
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Domino Data Lab
No answers on this topic
Alternatives Considered
Cloudera
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 pretty fast (unlike MS). As its a new product, I expect MS to be more efficient in handling customers questions.
Bharadwaj (Brad) Chivukula | TrustRadius Reviewer
Bharadwaj (Brad) Chivukula
Sr.Technical Manager/Delivery Manager
Read full review
Domino Data Lab
No answers on this topic
Return on Investment
Cloudera
  • Paid off for demonstration purposes.
Verified User
Anonymous
Read full review
Domino Data Lab
No answers on this topic
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.