What users are saying about
16 Ratings
Top Rated
110 Ratings
16 Ratings
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Score 9.2 out of 100
Top Rated
110 Ratings
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Score 8.9 out of 100

Feature Set Ratings

  • Dataiku DSS ranks higher in 4 feature sets: Platform Connectivity, Data Exploration, Data Preparation, Model Deployment
  • Jupyter Notebook ranks higher in 1 feature set: Platform Data Modeling

Platform Connectivity

9.1

Dataiku DSS

91%
8.4

Jupyter Notebook

84%
Dataiku DSS ranks higher in 3/4 features

Connect to Multiple Data Sources

10.0
100%
4 Ratings
8.7
87%
23 Ratings

Extend Existing Data Sources

9.9
99%
4 Ratings
8.9
89%
22 Ratings

Automatic Data Format Detection

9.9
99%
4 Ratings
8.7
87%
16 Ratings

MDM Integration

6.5
65%
2 Ratings
7.6
76%
17 Ratings

Data Exploration

9.7

Dataiku DSS

97%
9.3

Jupyter Notebook

93%
Dataiku DSS ranks higher in 2/2 features

Visualization

9.7
97%
4 Ratings
9.4
94%
23 Ratings

Interactive Data Analysis

9.8
98%
4 Ratings
9.2
92%
23 Ratings

Data Preparation

9.8

Dataiku DSS

98%
8.7

Jupyter Notebook

87%
Dataiku DSS ranks higher in 4/4 features

Interactive Data Cleaning and Enrichment

9.9
99%
4 Ratings
9.1
91%
22 Ratings

Data Transformations

9.9
99%
4 Ratings
8.8
88%
23 Ratings

Data Encryption

9.7
97%
4 Ratings
8.4
84%
16 Ratings

Built-in Processors

9.9
99%
4 Ratings
8.7
87%
15 Ratings

Platform Data Modeling

8.7

Dataiku DSS

87%
8.8

Jupyter Notebook

88%
Dataiku DSS ranks higher in 3/4 features

Multiple Model Development Languages and Tools

5.4
54%
4 Ratings
8.9
89%
22 Ratings

Automated Machine Learning

9.8
98%
4 Ratings
9.0
90%
20 Ratings

Single platform for multiple model development

9.8
98%
4 Ratings
9.0
90%
23 Ratings

Self-Service Model Delivery

9.8
98%
4 Ratings
8.4
84%
22 Ratings

Model Deployment

8.9

Dataiku DSS

89%
8.8

Jupyter Notebook

88%
Dataiku DSS ranks higher in 2/2 features

Flexible Model Publishing Options

8.9
89%
4 Ratings
8.8
88%
21 Ratings

Security, Governance, and Cost Controls

8.9
89%
4 Ratings
8.7
87%
20 Ratings

Attribute Ratings

  • Dataiku DSS is rated higher in 2 areas: Likelihood to Recommend, Support Rating
  • Dataiku DSS and Jupyter Notebook are tied in 1 area: Usability

Likelihood to Recommend

9.8

Dataiku DSS

98%
4 Ratings
9.1

Jupyter Notebook

91%
24 Ratings

Usability

10.0

Dataiku DSS

100%
1 Rating
10.0

Jupyter Notebook

100%
1 Rating

Support Rating

9.3

Dataiku DSS

93%
3 Ratings
9.0

Jupyter Notebook

90%
1 Rating

Likelihood to Recommend

Dataiku

Dataiku DSS is very well suited to handle large datasets and projects which requires a huge team to deliver results. This allows users to collaborate with each other while working on individual tasks. The workflow is easily streamlined and every action is backed up, allowing users to revert to specific tasks whenever required. While Dataiku DSS works seamlessly with all types of projects dealing with structured datasets, I haven't come across projects using Dataiku dealing with images/audio signals. But a workaround would be to store the images as vectors and perform the necessary tasks.
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Open Source

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.
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Pros

Dataiku

  • The intuitiveness of this tool is very good.
  • Click or Code - If you are a coder, you can code. If you are a manager, you can wrangle with data with visuals
  • The way you can control things, the set of APIs gives a lot of flexibility to a developer.
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Open Source

  • 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
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Cons

Dataiku

  • End product deployment.
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Open Source

  • 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.
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Pricing Details

Dataiku DSS

Starting Price

$0

Editions & Modules

Dataiku DSS editions and modules pricing
EditionModules
DiscoverContact sales team1
BusinessContact sales team2
EnterpriseContact sales team3

Offerings

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services

Entry-level set up fee?

No setup fee

Additional Details

Jupyter Notebook

Starting Price

Editions & Modules

Jupyter Notebook editions and modules pricing
EditionModules

Footnotes

    Offerings

    Free Trial
    Free/Freemium Version
    Premium Consulting/Integration Services

    Entry-level set up fee?

    No setup fee

    Additional Details

    Usability

    Dataiku

    As I have described earlier, the intuitiveness of this tool makes it great as well as the variety of users that can use this tool. Also, the plugins available in their repository provide solutions to various data science problems.
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    Open Source

    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.
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    Support Rating

    Dataiku

    The support team is very helpful, and even when we discover the missing features, after providing enough rational reasons and requirements, they put into it their development pipeline for the future release.
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    Open Source

    I haven't had a need to contact support. However, all required help is out there in public forums.
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    Alternatives Considered

    Dataiku

    Strictly for Data Science operations, Anaconda can be considered as a subset of Dataiku DSS. While Anaconda supports Python and R programming languages, Dataiku also provides this facility, but also provides GUI to creates models with just a click of a button. This provides the flexibility to users who do not wish to alter the model hyperparameters in greater depths. Writing codes to extract meaningful data is time consuming compared to Dataiku's ability to perform feature engineering and data transformation through click of a button.
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    Open Source

    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.
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    Return on Investment

    Dataiku

    • Given its open source status, only cost is the learning curve, which is minimal compared to time savings for data exploration.
    • Platform also ease tracking of data processing workflow, unlike Excel.
    • Build-in data visualizations covers many use cases with minimal customization; time saver.
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    Open Source

    • 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

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