Dataiku vs. Wolfram Mathematica

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Dataiku
Score 8.6 out of 10
N/A
Dataiku is a French startup and its product, DSS, is a challenger to market incumbents and features some visual tools to assist in building workflows.N/A
Mathematica
Score 8.2 out of 10
N/A
Wolfram's flagship product Mathematica is a modern technical computing application featuring a flexible symbolic coding language and a wide array of graphing and data visualization capabilities.
$1,520
per year
Pricing
DataikuWolfram Mathematica
Editions & Modules
Discover
Contact sales team
Business
Contact sales team
Enterprise
Contact sales team
Standard Cloud
$1,520
per year
Standard Desktop
$3,040
one-time fee
Standard Desktop & Cloud
$3,344
one-time fee
Mathematica Enterprise Edition
$8,150.00
one-time fee
Offerings
Pricing Offerings
DataikuMathematica
Free Trial
YesNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsDiscounts available for students and educational institutions. The Network Edition reduce per-user license costs through shared deployment across any number of machines on a local-area network.
More Pricing Information
Features
DataikuWolfram Mathematica
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Dataiku
9.1
4 Ratings
7% above category average
Wolfram Mathematica
-
Ratings
Connect to Multiple Data Sources10.04 Ratings00 Ratings
Extend Existing Data Sources10.04 Ratings00 Ratings
Automatic Data Format Detection10.04 Ratings00 Ratings
MDM Integration6.52 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Dataiku
10.0
4 Ratings
17% above category average
Wolfram Mathematica
-
Ratings
Visualization9.94 Ratings00 Ratings
Interactive Data Analysis10.04 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Dataiku
10.0
4 Ratings
19% above category average
Wolfram Mathematica
-
Ratings
Interactive Data Cleaning and Enrichment10.04 Ratings00 Ratings
Data Transformations10.04 Ratings00 Ratings
Data Encryption10.04 Ratings00 Ratings
Built-in Processors10.04 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Dataiku
8.7
4 Ratings
2% above category average
Wolfram Mathematica
-
Ratings
Multiple Model Development Languages and Tools5.14 Ratings00 Ratings
Automated Machine Learning10.04 Ratings00 Ratings
Single platform for multiple model development10.04 Ratings00 Ratings
Self-Service Model Delivery10.04 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Dataiku
9.0
4 Ratings
5% above category average
Wolfram Mathematica
-
Ratings
Flexible Model Publishing Options9.04 Ratings00 Ratings
Security, Governance, and Cost Controls9.04 Ratings00 Ratings
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Dataiku
-
Ratings
Wolfram Mathematica
9.9
6 Ratings
16% above category average
Pixel Perfect reports00 Ratings9.84 Ratings
Customizable dashboards00 Ratings9.94 Ratings
Report Formatting Templates00 Ratings9.96 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Dataiku
-
Ratings
Wolfram Mathematica
9.9
9 Ratings
21% above category average
Drill-down analysis00 Ratings9.98 Ratings
Formatting capabilities00 Ratings9.98 Ratings
Integration with R or other statistical packages00 Ratings9.97 Ratings
Report sharing and collaboration00 Ratings9.99 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Dataiku
-
Ratings
Wolfram Mathematica
9.3
8 Ratings
11% above category average
Publish to Web00 Ratings9.97 Ratings
Publish to PDF00 Ratings9.08 Ratings
Report Versioning00 Ratings9.97 Ratings
Report Delivery Scheduling00 Ratings8.95 Ratings
Delivery to Remote Servers00 Ratings8.95 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Dataiku
-
Ratings
Wolfram Mathematica
9.9
9 Ratings
19% above category average
Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings9.99 Ratings
Location Analytics / Geographic Visualization00 Ratings9.98 Ratings
Predictive Analytics00 Ratings9.98 Ratings
Best Alternatives
DataikuWolfram Mathematica
Small Businesses
IBM SPSS Modeler
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Score 7.8 out of 10
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Score 7.8 out of 10
Medium-sized Companies
Mathematica
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Score 8.2 out of 10
Entrinsik Informer
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Score 9.3 out of 10
Enterprises
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All AlternativesView all alternativesView all alternatives
User Ratings
DataikuWolfram Mathematica
Likelihood to Recommend
10.0
(4 ratings)
9.9
(9 ratings)
Usability
10.0
(1 ratings)
-
(0 ratings)
Support Rating
9.4
(3 ratings)
9.5
(2 ratings)
User Testimonials
DataikuWolfram Mathematica
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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Wolfram
We are the judgement that Wolfram Mathematica is despite many critics based on the paradigms selected a mark in the fields of the markets for computations of all kind. Wolfram Mathematica is even a choice in fields where other bolide systems reign most of the market. Wolfram Mathematica offers rich flexibility and internally standardizes the right methodologies for his user community. Wolfram Mathematica is not cheap and in need of a hard an long learner journey. That makes it weak in comparison with of-the-shelf-solution packages or even other programming languages. But for systematization of methods Wolfram Mathematica is far in front of almost all the other. Scientist and interested people are able to develop themself further and Wolfram Matheamatica users are a human variant for themself. The reach out for modern mathematics based science is deep and a unique unified framework makes the whole field of mathematics accessable comparable to the brain of Albert Einstein. The paradigms incorporated are the most efficients and consist in assembly on the market. The mathematics is covering and fullfills not just education requirements but the demands and needs of experts.
Mathematica is incompatible with other systems for mCAx and therefore the borders between the systems are hard to overcome. Wolfram Mathematica should be consider one of the more open systems because other code can be imported and run but on the export side it is rathe incompatible by design purposes. A better standard for all that might solve the crisis but there is none in sight. Selection of knowledge of what works will be in the future even more focussed and general system might be one the lossy side. Knowledge of esthetics of what will be in the highest demand in necessary and Wolfram is not a leader in this field of science. Mathematics leves from gathering problems from application fields and less from the glory of itself and the formalization of this.
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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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Wolfram
  • It allows straightforward integration of analytic analysis of algebraic expressions and their numerical implemented.
  • Supports varying programmatic paradigms, so one can choose what best fits the problem or task: pure functions, procedural programming, list processing, and even (with a bit of setup) object-oriented programming.
  • The extensive and rich tools for graphical rendering make it very easy to not just get 2D and 3D renderings of final output, but also to do quick-and-dirty 2D and 3D rendering of intermediate results and/or debugging results.
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Cons
Dataiku
  • End product deployment.
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Wolfram
  • Should include more libraries and functions.
  • Should include more functions that can be used in Machine Learning.
  • Should include more functions that can be used in Data Science.
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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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Wolfram
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.
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Wolfram
Wolfram Mathematica is a nice software package. It has very nice features and easy to install and use in your machine. Besides this, there is a nice support from Wolfram. They come to the university frequently to give seminars in Mathematica. I think this is the best thing they are doing. That is very helpful for graduate and undergraduate students who are using Mathematica in their research.
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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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Wolfram
We have evaluated and are using in some cases the Python language in concert with the Jupyter notebook interface. For UI, we using libraries like React to create visually stunning visualizations of such models. Mathematica compares favorably to this alternative in terms of speed of development. Mathematica compares unfavorably to this alternative in terms of license costs.
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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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Wolfram
  • Easy to solve huge mathematical equations, so it saved time there
  • Doing analysis and plotting graphs is also another plus point
  • Learning is very slow, and it took lot of time to learn its scripting language
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ScreenShots