Cloudera

I like Cloudera’s ease of use and easy set up. I can easily diagnose some problems with the cluster thru GUI. Hbase and Spark Integration were also great for our needs. Integrationthrough Kafka has also helped us test new features in application thereby improving performance. The metrics really gives us idea about clusters health and reduces surprises.

Management console and support services are quite expensive in the moment you scale it up. We can also hardly figure some small set up that is related to our old system. SparkSQL isn’t fully supported and it might be better if they could replicate production environment closely as much as possible.

Cloudera contains all the components that will help us create DataHub. It also has an excellent support of the platform and it is open source which allows our data to be customized in our own format. It also has great management capabilities through Cloudera Manager. All in all, it is a great platform.

The Cloudera software comes with exceptional and excellent management capabilities for business users. It actually does not place restrictions on data because it is open source and presents end users with an array of components to help build a solid data hub. It has an amazing dashboard that comes with a well centralized configuration function. However users can be pleased with the platform as it come with a wide range of products and tools with the capacity to run on frameworks like MapReduce and so on.

The platform has compatibility issues with product installation on other OS except for Linux. A used must have an excellent knowledge of Linux commands to be able to find their way around it. You need to invest a lot of time in installation until the exact version is matched and GUI’s are practically missing. A user will have to toggle through a lot of documentation, regardless of how easy it is to locate. I would advise the vendors to make for more flexible pricing.

An advanced user platform that is easy to install even on virtual machines and all of its products with latest versions are readily available. Users will find this platform a lot more accommodating as it has the ability to eliminate the possibility of manual error executing complex administration tasks. Cloudera can work or be deployed across multiple server blades and can be used between a company’s product development and its analytics team. It has one of the fastest response time. I gladly recommend it.

-Extensive variety of Products accessible on Cloudera which keeps running on MapReduce structure. -Simple to introduce on Virtual Machines. Every one of the items are accessible on the site and ventures for establishment are effectively accessible and all around archived with cases and case situations. -Every one of the items with most recent variants are accessible which can be effortlessly introduced by means of yum. -Cloudera Impala which the speediest approach to question the HDFS without utilizing MapReduce system. This is uninhibitedly accessible on their site while with Amazon EC2 machines and Windows Azure you need to shell some cash for utilizing their machine.

Couple of little setup that are exceptionally coordinated to our old framework were difficult to make sense of. A tiny bit more documentation is required. SparkSQL is not completely bolstered and there is no chance to get for us to overhaul an individual segment our-self. The change on area of libraries from the given virtual-box picture to the creation environment brought about little issues. It may be better if the VM could reproduce the creation environment as close as could be expected under the circumstances.

I utilized the Cloudera Enterprise as a part of my past organization wherein I needed to utilized the Cloudera Impala item. I have additionally utilized Cloudera Hadoop, Hive, Sqoop, Pig, Mahout and so on. Since my undertaking had necessity for attempting diverse instruments accessible in business sector, we were doing research on which device is the best, thats where we arrived on Cloudera Enterprise items. It is utilized just as a part of my specialization. To address the shareholder information in records from various suppliers which should be prepared by means of MapReduce structure.