Cloudera Data Science Workbench vs. Wolfram Mathematica

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Data Science Workbench
Score 6.7 out of 10
N/A
Cloudera Data Science Workbench enables secure self-service data science for the enterprise. It is a collaborative environment where developers can work with a variety of libraries and frameworks.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
Cloudera Data Science WorkbenchWolfram Mathematica
Editions & Modules
No answers on this topic
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
Data Science WorkbenchMathematica
Free Trial
NoNo
Free/Freemium Version
NoNo
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
Community Pulse
Cloudera Data Science WorkbenchWolfram Mathematica
Top Pros
Top Cons
Features
Cloudera Data Science WorkbenchWolfram Mathematica
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Cloudera Data Science Workbench
7.5
2 Ratings
12% below category average
Wolfram Mathematica
-
Ratings
Connect to Multiple Data Sources7.02 Ratings00 Ratings
Extend Existing Data Sources8.02 Ratings00 Ratings
Automatic Data Format Detection7.02 Ratings00 Ratings
MDM Integration8.02 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Cloudera Data Science Workbench
7.6
2 Ratings
10% below category average
Wolfram Mathematica
-
Ratings
Visualization7.12 Ratings00 Ratings
Interactive Data Analysis8.02 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Cloudera Data Science Workbench
7.8
2 Ratings
6% below category average
Wolfram Mathematica
-
Ratings
Interactive Data Cleaning and Enrichment7.02 Ratings00 Ratings
Data Transformations8.02 Ratings00 Ratings
Data Encryption8.02 Ratings00 Ratings
Built-in Processors8.02 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Cloudera Data Science Workbench
7.6
2 Ratings
11% below category average
Wolfram Mathematica
-
Ratings
Multiple Model Development Languages and Tools8.02 Ratings00 Ratings
Automated Machine Learning7.01 Ratings00 Ratings
Single platform for multiple model development7.12 Ratings00 Ratings
Self-Service Model Delivery8.12 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Cloudera Data Science Workbench
8.0
2 Ratings
7% below category average
Wolfram Mathematica
-
Ratings
Flexible Model Publishing Options8.12 Ratings00 Ratings
Security, Governance, and Cost Controls7.82 Ratings00 Ratings
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Cloudera Data Science Workbench
-
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
Cloudera Data Science Workbench
-
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
Cloudera Data Science Workbench
-
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
Cloudera Data Science Workbench
-
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
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Cloudera Data Science WorkbenchWolfram Mathematica
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Enterprises
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User Ratings
Cloudera Data Science WorkbenchWolfram Mathematica
Likelihood to Recommend
9.0
(3 ratings)
9.9
(9 ratings)
Support Rating
7.9
(2 ratings)
9.5
(2 ratings)
User Testimonials
Cloudera Data Science WorkbenchWolfram Mathematica
Likelihood to Recommend
Cloudera
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.
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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
Cloudera
  • 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
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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
Cloudera
  • Installation is difficult.
  • Upgrades are difficult.
  • Licensing options are not flexible.
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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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Support Rating
Cloudera
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.
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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
Cloudera
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.
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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
Cloudera
  • Paid off for demonstration purposes.
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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