What users are saying about
16 Ratings
10 Ratings
16 Ratings
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Score 9.2 out of 100
10 Ratings
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Score 8.7 out of 100

Feature Set Ratings

  • Dataiku DSS ranks higher in 3 feature sets: Platform Connectivity, Data Exploration, Data Preparation
  • H2O ranks higher in 2 feature sets: Platform Data Modeling, Model Deployment

Platform Connectivity

9.1

Dataiku DSS

91%
8.0

H2O

80%
Dataiku DSS ranks higher in 4/4 features

Connect to Multiple Data Sources

10.0
100%
4 Ratings
8.0
80%
1 Rating

Extend Existing Data Sources

9.9
99%
4 Ratings
N/A
0 Ratings

Automatic Data Format Detection

9.9
99%
4 Ratings
8.0
80%
1 Rating

MDM Integration

6.5
65%
2 Ratings
N/A
0 Ratings

Data Exploration

9.7

Dataiku DSS

97%
8.5

H2O

85%
Dataiku DSS ranks higher in 2/2 features

Visualization

9.7
97%
4 Ratings
8.0
80%
1 Rating

Interactive Data Analysis

9.8
98%
4 Ratings
9.0
90%
1 Rating

Data Preparation

9.8

Dataiku DSS

98%
9.3

H2O

93%
Dataiku DSS ranks higher in 3/4 features

Interactive Data Cleaning and Enrichment

9.9
99%
4 Ratings
10.0
100%
1 Rating

Data Transformations

9.9
99%
4 Ratings
9.0
90%
1 Rating

Data Encryption

9.7
97%
4 Ratings
N/A
0 Ratings

Built-in Processors

9.8
98%
4 Ratings
9.0
90%
1 Rating

Platform Data Modeling

8.7

Dataiku DSS

87%
10.0

H2O

100%
H2O ranks higher in 4/4 features

Multiple Model Development Languages and Tools

5.4
54%
4 Ratings
10.0
100%
1 Rating

Automated Machine Learning

9.8
98%
4 Ratings
10.0
100%
1 Rating

Single platform for multiple model development

9.8
98%
4 Ratings
10.0
100%
1 Rating

Self-Service Model Delivery

9.8
98%
4 Ratings
10.0
100%
1 Rating

Model Deployment

8.9

Dataiku DSS

89%
9.0

H2O

90%
Dataiku DSS ranks higher in 1/2 features

Flexible Model Publishing Options

8.9
89%
4 Ratings
10.0
100%
1 Rating

Security, Governance, and Cost Controls

8.9
89%
4 Ratings
8.0
80%
1 Rating

Attribute Ratings

  • Dataiku DSS is rated higher in 2 areas: Likelihood to Recommend, Support Rating

Likelihood to Recommend

9.8

Dataiku DSS

98%
4 Ratings
8.1

H2O

81%
3 Ratings

Usability

10.0

Dataiku DSS

100%
1 Rating

H2O

N/A
0 Ratings

Support Rating

9.3

Dataiku DSS

93%
3 Ratings
9.0

H2O

90%
2 Ratings

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.
Read full review

H2O.ai

Most suited if in little time you wanted to build and train a model. Then, H2O makes life very simple. It has support with R, Python and Java, so no programming dependency is required to use it. It's very simple to use. If you want to modify or tweak your ML algorithm then H2O is not suitable. You can't develop a model from scratch.
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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.
Read full review

H2O.ai

  • Excellent analytical and prediction tool
  • In the beginning, usage of H20 Flow in Web UI enables quick development and sharing of the analytical model
  • Readily available algorithms, easy to use in your analytical projects
  • Faster than Python scikit learn (in machine learning supervised learning area)
  • It can be accessed (run) from Python, not only JAVA etc.
  • Well documented and suitable for fast training or self studying
  • In the beginning, one can use the clickable Flow interface (WEB UI) and later move to a Python console. There is then no need to click in H20 Flow
  • It can be used as open source
Read full review

Cons

Dataiku

  • End product deployment.
Read full review

H2O.ai

  • Better documentation
  • Improve the Visual presentations including charting etc
Read full review

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

H2O

Starting Price

Editions & Modules

H2O 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.
    Read full review

    H2O.ai

    No answers on this topic

    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.
    Read full review

    H2O.ai

    The overall experience I have with H2O is really awesome, even with its cost effectiveness.
    Read full review

    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.
    Read full review

    H2O.ai

    Both are open source (though H2O only up to some level). Both comprise of deep learning, but H2O is not focused directly on deep learning, while Tensor Flow has a "laser" focus on deep learning. H2O is also more focused on scalability. H2O should be looked at not as a competitor but rather a complementary tool. The use case is usually not only about the algorithms, but also about the data model and data logistics and accessibility. H2O is more accessible due to its UI. Also, both can be accessed from Python. The community around TensorFlow seems larger than that of H2O.
    Read full review

    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.
    Read full review

    H2O.ai

    • Positive impact: saving in infrastructure expenses - compared to other bulky tools this costs a fraction
    • Positive impact: ability to get quick fixes from H2O when problems arise - compared to waiting for several months/years for new releases from other vendors
    • Positive impact: Access to H2O core team and able to get features that are needed for our business quickly added to the core H2O product
    Read full review

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