Cloudera Distribution for Hadoop Reviews

We are in the testing phase of Cloudera Distribution for Hadoop, and we will be in production soon.

The procedure for operations could be simplified.

I have used Cloudera Distribution for Hadoop within the past 12 months.

The solution is reliable and stable, it fits our requirements.

The implementation of Cloudera Distribution for Hadoop is not easy. It works on multiple nodes and can be complex for testing. The whole process took us one and a half days.

We used a local system integrator for the implementation. We had approximately five people for the implementation.

We have not had to do maintenance of the solution because we are still in the testing phase.

My advice to others is this solution can be complex.

I rate Cloudera Distribution for Hadoop a seven out of ten.

We use the solution to maintain our legacy data warehouse for better performance and more extensive storage.

The solution's most valuable feature is the enterprise data platform.

They should work on the solution's pricing. Also, finding resources with good experience in the solution is difficult. Thus, they should upgrade their technical capabilities in the market. 

They should add features like AutoML and AutoDev for enhanced machine-learning experiences. In addition, they should consider developing an integration capability similar to Informatica for an end-to-end enterprise solution.

We have been using the solution for one year.

The solution's customer support team could be better. We received their assistance only with installation and configuration.

The solution is expensive. The license costs around 10k.

Cloudera is a cost-effective solution if you need more storage space. In this case, I advise you to opt for it. I rate the solution as an eight out of ten.

We mostly use the solution for big data analytics, data sharing, and reporting.

Cloudera, as a whole, is designed to provide organizations with solutions for big data. Cloudera is not one single component. It has many components related to storage, analytics, queries, and processing. All of these components work together to support big data implementation and analytics.

The performance of some analytics engines provided by Cloudera is not that good. So, we are using other analytics tools besides Cloudera.

I have been using the solution for more than four years.

We also use other tools like DataIQ and Apache Kudu.

I'm working with the solution myself. As a company, we are implementing it for other customers. Cloudera itself does not provide analytics. It prepares data for analytics tools that work with Big Data, such as Apache Spark, DataIQ, and Tableau.

Overall, I rate the solution a nine out of ten.