Cloudera Distribution Hadoop (CDH) vs. VMware Tanzu Data Services (Greenplum, GemFire, RabbitMQ, Tanzu SQL)

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Cloudera Distribution Hadoop (CDH)
Score 6.3 out of 10
N/A
CDH is Cloudera’s 100% open source platform distribution, including Apache Hadoop and built specifically to meet enterprise demands. CDH delivers everything needed for enterprise use right out of the box. By integrating Hadoop with more than a dozen other critical open source projects, Cloudera has created a functionally advanced system that helps you perform end-to-end Big Data workflows.N/A
VMware Tanzu Data Services
Score 8.3 out of 10
N/A
VMware Tanzu Data Services is a portfolio of on-demand caching, messaging, and database software on VMware Tanzu for development teams building modern applications.N/A
Pricing
Cloudera Distribution Hadoop (CDH)VMware Tanzu Data Services (Greenplum, GemFire, RabbitMQ, Tanzu SQL)
Editions & Modules
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Offerings
Pricing Offerings
Cloudera Distribution Hadoop (CDH)VMware Tanzu Data Services
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 Distribution Hadoop (CDH)VMware Tanzu Data Services (Greenplum, GemFire, RabbitMQ, Tanzu SQL)
Top Pros
Top Cons
Best Alternatives
Cloudera Distribution Hadoop (CDH)VMware Tanzu Data Services (Greenplum, GemFire, RabbitMQ, Tanzu SQL)
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No answers on this topic

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Score 9.3 out of 10
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User Ratings
Cloudera Distribution Hadoop (CDH)VMware Tanzu Data Services (Greenplum, GemFire, RabbitMQ, Tanzu SQL)
Likelihood to Recommend
7.0
(1 ratings)
8.0
(1 ratings)
Support Rating
-
(0 ratings)
8.0
(1 ratings)
User Testimonials
Cloudera Distribution Hadoop (CDH)VMware Tanzu Data Services (Greenplum, GemFire, RabbitMQ, Tanzu SQL)
Likelihood to Recommend
Cloudera
Cloudera Distribution Hadoop (CDH) does a lot of things really well - especially on the analytical front. That being said the product is quite expensive. There are seemingly numerous applications that do the same thing on the functional level that are much more cost effecient for enterprise teams. If I were recommending this to a colleague I would let them know the product will absolutely be able to get the job done for their use case, but there are more efficient options
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VMware
If you need to execute ml algorithms, learning techniques, or mathematical calculations on large amounts of heterogeneous data, VMware Tanzu Data Services will be ideal. It will be really simple to set up, particularly if you choose AWS as your integrated cloud provider. However, if you're working with lower data amounts, such as gigabytes, it can be superfluous.
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Pros
Cloudera
  • Solid and robust set of integrations
  • Easy to use and easy to deploy across the enterprise
  • Reliability - never lost any info
  • Simple and clean interface
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VMware
  • Apache MADlib provides popular machine learning functionality.
  • Allows you to query terabytes of data databases.
  • Interoperability for AWS S3 is effortless.
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Cons
Cloudera
  • The price is quite high competitively speaking
  • Hard to learn more robust functions and custom options without experience
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VMware
  • Running on Azure is a little more difficult.
  • Synchronization with Kafka may be a little easier.
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Support Rating
Cloudera
No answers on this topic
VMware
They were very helpful. We needed support for initial implementation.
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Alternatives Considered
Cloudera
In terms of functionality there's not much difference, both get the job done. Amazon was more cost-efficient for our team, but this could vary depending on the size of the business. One thing I did notice was that Cloudera seemed to management and spit out our deployments faster than AWS.
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VMware
No answers on this topic
Return on Investment
Cloudera
  • Saves time by automating typically manual processes (data management, lifecyle AI etc)
  • Quick deployments and analytics allow for faster time-to-value
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VMware
  • There was a noticeable reduction in system reliability.
  • Saw a reduction in unsuccessful analytics operations.
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ScreenShots