What users are saying about
15 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow noopener noreferrer'>trScore algorithm: Learn more.</a>
Score 8.3 out of 100
13 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow noopener noreferrer'>trScore algorithm: Learn more.</a>
Score 7.4 out of 100

Likelihood to Recommend

Amazon SageMaker

Amazon SageMaker is a great tool for developing machine learning models that take more effort than just point-and-click type of analyses. The software works well with the other tools in the Amazon ecosystem, so if you use Amazon Web Services or are thinking about it, SageMaker would be a great addition. SageMaker is great for consumer insights, predictive analytics, and looking for gems of insight in the massive amounts of data we create. SageMaker is less suitable for analysts who do generally "small" data analyses, and "small" data analyses in today's world can be billions of records.
Thomas Young | TrustRadius Reviewer

Data Science Workbench

  • 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.
Bharadwaj (Brad) Chivukula | TrustRadius Reviewer

Feature Rating Comparison

Platform Connectivity

Amazon SageMaker
Data Science Workbench
7.0
Connect to Multiple Data Sources
Amazon SageMaker
Data Science Workbench
6.0
Extend Existing Data Sources
Amazon SageMaker
Data Science Workbench
7.0
Automatic Data Format Detection
Amazon SageMaker
Data Science Workbench
7.0
MDM Integration
Amazon SageMaker
Data Science Workbench
8.0

Data Exploration

Amazon SageMaker
Data Science Workbench
9.0
Visualization
Amazon SageMaker
Data Science Workbench
9.0
Interactive Data Analysis
Amazon SageMaker
Data Science Workbench
9.0

Data Preparation

Amazon SageMaker
Data Science Workbench
7.8
Interactive Data Cleaning and Enrichment
Amazon SageMaker
Data Science Workbench
8.0
Data Transformations
Amazon SageMaker
Data Science Workbench
8.0
Data Encryption
Amazon SageMaker
Data Science Workbench
8.0
Built-in Processors
Amazon SageMaker
Data Science Workbench
7.0

Platform Data Modeling

Amazon SageMaker
Data Science Workbench
9.7
Multiple Model Development Languages and Tools
Amazon SageMaker
Data Science Workbench
9.0
Single platform for multiple model development
Amazon SageMaker
Data Science Workbench
10.0
Self-Service Model Delivery
Amazon SageMaker
Data Science Workbench
10.0

Model Deployment

Amazon SageMaker
Data Science Workbench
7.0
Flexible Model Publishing Options
Amazon SageMaker
Data Science Workbench
10.0
Security, Governance, and Cost Controls
Amazon SageMaker
Data Science Workbench
4.0

Pros

Amazon SageMaker

  • Provides enough freedom for experienced data scientists and also for those who just need things done without going much deeper into building models.
  • Customization and easy to alter and change.
  • If you already are an Amazon user, you do not need to transition over to another software.
Anonymous | TrustRadius Reviewer

Data Science Workbench

  • The ability to use multiple languages.
  • GitHub integration.
  • Scalable.
Anonymous | TrustRadius Reviewer

Cons

Amazon SageMaker

  • It's very good for the hardcore programmer, but a little bit complex for a data scientist or new hire who does not have a strong programming background.
  • Most of the popular library and ML frameworks are there, but we still have to depend on them for new releases.
Anonymous | TrustRadius Reviewer

Data Science Workbench

  • 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
Bharadwaj (Brad) Chivukula | TrustRadius Reviewer

Support Rating

Amazon SageMaker

No score
No answers yet
No answers on this topic

Data Science Workbench

Data Science Workbench 5.0
Based on 1 answer
It is expensive and difficult to install and maintain.
Anonymous | TrustRadius Reviewer

Alternatives Considered

Amazon SageMaker

Amazon SageMaker took the heavy lifting out of building and creating models. It allowed for our organization to use our current system for integration and essentially added on a feature to help all levels of Data scientists and IT professionals in our department and company as a whole. The training was simple as well.
Anonymous | TrustRadius Reviewer

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 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

Return on Investment

Amazon SageMaker

  • We have been able to deliver data products more rapidly because we spend less time building data pipelines and model servers.
  • We can prototype more rapidly because it is easy to configure notebooks to access AWS resources.
  • For our use-cases, serving models is less expensive with SageMaker than bespoke servers.
Gavin Hackeling | TrustRadius Reviewer

Data Science Workbench

  • Paid off for demonstration purposes.
Anonymous | TrustRadius Reviewer

Pricing Details

Amazon SageMaker

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Data Science Workbench

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

Rating Summary

Likelihood to Recommend

Amazon SageMaker
8.3
Data Science Workbench
6.1

Support Rating

Amazon SageMaker
Data Science Workbench
5.0

Add comparison