What users are saying about

Data Science Workbench vs Jupyter Notebook

Data Science Workbench
14 Ratings
Jupyter Notebook
<a href='https://www.trustradius.com/static/about-trustradius-scoring#question3' target='_blank' rel='nofollow noopener'>Customer Verified: Read more.</a>
Top Rated
99 Ratings

Data Science Workbench

14 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow noopener'>trScore algorithm: Learn more.</a>
Score 7.3 out of 100

Based on 14 reviews and ratings

Jupyter Notebook

<a href='https://www.trustradius.com/static/about-trustradius-scoring#question3' target='_blank' rel='nofollow noopener'>Customer Verified: Read more.</a>
Top Rated
99 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow noopener'>trScore algorithm: Learn more.</a>
Score 8.8 out of 100

Based on 99 reviews and ratings

Feature Set Ratings

  • Jupyter Notebook ranks higher in 5 feature sets: Platform Connectivity, Data Exploration, Data Preparation, Platform Data Modeling, Model Deployment

Platform Connectivity

7.5

Data Science Workbench

75%
8.3

Jupyter Notebook

83%
Jupyter Notebook ranks higher in 3/4 features
Jupyter Notebook ranks higher in 3/4 features

Connect to Multiple Data Sources

7.0
70%
2 Ratings
8.5
85%
23 Ratings

Extend Existing Data Sources

8.0
80%
2 Ratings
8.6
86%
22 Ratings

Automatic Data Format Detection

7.0
70%
2 Ratings
8.5
85%
16 Ratings

MDM Integration

8.0
80%
2 Ratings
7.5
75%
17 Ratings

Data Exploration

7.6

Data Science Workbench

76%
9.2

Jupyter Notebook

92%
Jupyter Notebook ranks higher in 2/2 features
Jupyter Notebook ranks higher in 2/2 features

Visualization

7.1
71%
2 Ratings
9.3
93%
23 Ratings

Interactive Data Analysis

8.0
80%
2 Ratings
9.0
90%
23 Ratings

Data Preparation

7.8

Data Science Workbench

78%
8.5

Jupyter Notebook

85%
Jupyter Notebook ranks higher in 4/4 features
Jupyter Notebook ranks higher in 4/4 features

Interactive Data Cleaning and Enrichment

7.0
70%
2 Ratings
8.9
89%
22 Ratings

Data Transformations

8.0
80%
2 Ratings
8.7
87%
23 Ratings

Data Encryption

8.0
80%
2 Ratings
8.1
81%
16 Ratings

Built-in Processors

8.0
80%
2 Ratings
8.4
84%
15 Ratings

Platform Data Modeling

7.6

Data Science Workbench

76%
8.7

Jupyter Notebook

87%
Jupyter Notebook ranks higher in 4/4 features
Jupyter Notebook ranks higher in 4/4 features

Multiple Model Development Languages and Tools

8.0
80%
2 Ratings
8.8
88%
22 Ratings

Automated Machine Learning

7.0
70%
1 Rating
8.8
88%
20 Ratings

Single platform for multiple model development

7.1
71%
2 Ratings
8.8
88%
23 Ratings

Self-Service Model Delivery

8.1
81%
2 Ratings
8.4
84%
22 Ratings

Model Deployment

8.0

Data Science Workbench

80%
8.6

Jupyter Notebook

86%
Jupyter Notebook ranks higher in 2/2 features
Jupyter Notebook ranks higher in 2/2 features

Flexible Model Publishing Options

8.1
81%
2 Ratings
8.6
86%
21 Ratings

Security, Governance, and Cost Controls

7.8
78%
2 Ratings
8.5
85%
20 Ratings

Attribute Ratings

  • Jupyter Notebook is rated higher in 2 areas: Likelihood to Recommend, Support Rating

Likelihood to Recommend

8.9

Data Science Workbench

89%
3 Ratings
9.1

Jupyter Notebook

91%
24 Ratings

Usability

Data Science Workbench

N/A
0 Ratings
10.0

Jupyter Notebook

100%
1 Rating

Support Rating

7.7

Data Science Workbench

77%
3 Ratings
9.0

Jupyter Notebook

90%
1 Rating

Likelihood to Recommend

Data Science Workbench

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.

Read full review

Anonymous | TrustRadius Reviewer
Verified User
View all 3 answers on this topic

Jupyter Notebook

I've created a number of daisy chain notebooks for different workflows, and every time, I create my workflows with other users in mind. Jupiter Notebook makes it very easy for me to outline my thought process in as granular a way as I want without using innumerable small. inline comments.

Read full review

Lindsay Veazey | TrustRadius Reviewer
Lindsay Veazey
View all 24 answers on this topic

Pros

Data Science Workbench

  • 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

Read full review

Bharadwaj (Brad) Chivukula | TrustRadius Reviewer
Bharadwaj (Brad) Chivukula
View all 3 answers on this topic

Jupyter Notebook

  • Code presentation- with Jupyter Notebook you can deploy codes and markdowns which makes the code easy to read and understand.
  • User interface- the user interface of the Jupyter Notebook is very smooth, there are a lot of easy shortcuts as well the icons to make our work easier
  • Server hosting- with Jupyter Notebook server hosting is very easy which adds to the security feature

Read full review

Aditya Kumar | TrustRadius Reviewer
Aditya Kumar
View all 24 answers on this topic

Cons

Data Science Workbench

  • Installation is difficult.
  • Upgrades are difficult.
  • Licensing options are not flexible.

Read full review

Anonymous | TrustRadius Reviewer
Verified User
View all 3 answers on this topic

Jupyter Notebook

  • Need more Hotkeys for creating a beautiful notebook. Sometimes we need to download other plugins which messes [with] its default settings.
  • Not as powerful as IDE, which sometimes makes [the] job difficult and allows duplicate code as it get confusing when the number of lines increases. Need a feature where [an] error comes if duplicate code is found or [if a] developer tries the same function name.

Read full review

Anonymous | TrustRadius Reviewer
Verified User
View all 24 answers on this topic

Pricing Details

Data Science Workbench

General

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

Starting Price

—

Jupyter Notebook

General

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

Starting Price

—

Usability

Data Science Workbench

No score
No answers yet
No answers on this topic

Jupyter Notebook

Jupyter Notebook 10.0
Based on 1 answer
Jupyter is highly simplistic. It took me about 5 mins to install and create my first "hello world" without having to look for help. The UI has minimalist options and is quite intuitive for anyone to become a pro in no time. The lightweight nature makes it even more likeable.

Read full review

Anonymous | TrustRadius Reviewer
Verified User
View all 1 answers on this topic

Support Rating

Data Science Workbench

Data Science Workbench 7.7
Based on 3 answers
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.

Read full review

Anonymous | TrustRadius Reviewer
Verified User
View all 3 answers on this topic

Jupyter Notebook

Jupyter Notebook 9.0
Based on 1 answer
I haven't had a need to contact support. However, all required help is out there in public forums.

Read full review

Anonymous | TrustRadius Reviewer
Verified User
View all 1 answers on this topic

Alternatives Considered

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.

Read full review

Bharadwaj (Brad) Chivukula | TrustRadius Reviewer
Bharadwaj (Brad) Chivukula
View all 3 answers on this topic

Jupyter Notebook

I have used PyCharm as well as Jupyter Notebook and for me, Jupyter wins almost every time. I really like its user-friend interface for someone who is new to python programming. The ability to run a big chunk of code part by part is a big game-changer for me. One thing I would like is a night mode just like PyCharm as it helps the night owls like myself who work a big part during the night. I also like how Anaconda command prompt helps you download a library and just a simple import statement in the notebook helps you extract every functionality.

Read full review

Rounak Verma | TrustRadius Reviewer
Rounak Verma
View all 24 answers on this topic

Return on Investment

Data Science Workbench

  • Paid off for demonstration purposes.

Read full review

Anonymous | TrustRadius Reviewer
Verified User
View all 3 answers on this topic

Jupyter Notebook

  • Positive impact: flexible implementation on any OS, for many common software languages
  • Positive impact: straightforward duplication for adaptation of workflows for other projects
  • Negative impact: sometimes encourages pigeonholing of data science work into notebooks versus extending code capability into software integration

Read full review

Lindsay Veazey | TrustRadius Reviewer
Lindsay Veazey
View all 24 answers on this topic

Add comparison