Cloudera Data Science Workbench vs. Kognitio

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
Kognitio
Score 9.1 out of 10
N/A
WX2 is the data and analytics focused data warehouse appliance solution from UK company Kognitio.N/A
Pricing
Cloudera Data Science WorkbenchKognitio
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Data Science WorkbenchKognitio
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Cloudera Data Science WorkbenchKognitio
Top Pros
Top Cons
Features
Cloudera Data Science WorkbenchKognitio
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
Kognitio
-
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
Kognitio
-
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
Kognitio
-
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
Kognitio
-
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
Kognitio
-
Ratings
Flexible Model Publishing Options8.12 Ratings00 Ratings
Security, Governance, and Cost Controls7.82 Ratings00 Ratings
Best Alternatives
Cloudera Data Science WorkbenchKognitio
Small Businesses
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10

No answers on this topic

Medium-sized Companies
Mathematica
Mathematica
Score 8.2 out of 10
Cloudera Manager
Cloudera Manager
Score 9.7 out of 10
Enterprises
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
IBM Analytics Engine
IBM Analytics Engine
Score 8.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Cloudera Data Science WorkbenchKognitio
Likelihood to Recommend
9.0
(3 ratings)
9.0
(2 ratings)
Support Rating
7.9
(2 ratings)
-
(0 ratings)
User Testimonials
Cloudera Data Science WorkbenchKognitio
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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Kognitio
What you have are different strategies for data encoding, which makes the process quite flexible, it is perfectly done so that a joint and collaborative work can be carried out, this information analyzed in large quantities, is extremely vital for the company, by giving it the correct and timely reading
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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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Kognitio
  • Ultra fast query results.
  • IN Memory Database.
  • Easy integration to reporting services.
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Cons
Cloudera
  • Installation is difficult.
  • Upgrades are difficult.
  • Licensing options are not flexible.
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Kognitio
  • Problems Could Be Encountered is particularly pronounced in more complex analyses.
  • Categorical variables are often not precise enough
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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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Kognitio
No answers on this topic
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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Kognitio
We selected Kognitio because of the legacy systems that are still running. Also, we have legacy systems in place that are fit for Kognitio. End-user has good feedback on our side when we started implementing this solution. Current servers are compatible with Kognitio in place.
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Return on Investment
Cloudera
  • Paid off for demonstration purposes.
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Kognitio
  • The implementation of the formats to integrate the users we have and the program is also good.
  • I also improve the control of aspects related to the work environment
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ScreenShots