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

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

Incentivized

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.

Incentivized

• 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

Incentivized

• Apache MADlib provides popular machine learning functionality.
• Allows you to query terabytes of data databases.
• Interoperability for AWS S3 is effortless.

Incentivized

• The price is quite high competitively speaking
• Hard to learn more robust functions and custom options without experience

Incentivized

• Running on Azure is a little more difficult.
• Synchronization with Kafka may be a little easier.

Incentivized

They were very helpful. We needed support for initial implementation.

Incentivized

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.

Incentivized

• Saves time by automating typically manual processes (data management, lifecyle AI etc)
• Quick deployments and analytics allow for faster time-to-value

Incentivized

• There was a noticeable reduction in system reliability.
• Saw a reduction in unsuccessful analytics operations.

Incentivized