We performed a comparison between Cloudera Distribution for Hadoop, Hortonworks Data Platform, and HPE Ezmeral Data Fabric based on real PeerSpot user reviews.
Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop.
"The tool can be deployed using different container technologies, which makes it very scalable."
"We experienced many issues when we started working with Hadoop 3.0 in the Cloudera 6.0 version, so there are a lot of things that need to improve. I believe they are working on that."
"The product provides better data processing features than other tools."
"The data science aspect of the solution is valuable."
"It is helpful to gather and process data."
"With a cluster available, you can manage the security layer using the shared SDX - it provides flexibility."
"The most valuable feature is Impala, the querying engine, which is very fast."
"It has the best proxy, security, and support features compared to open-source products."
"The upgrades and patches must come from Hortonworks."
"Distributed computing, secure containerization, and governance capabilities are the most valuable features."
"The data platform is pretty neat. The workflow is also really good."
"It is a scalable platform."
"The Hortonworks solution is so stable. It is working as a production system, without any error, without any downtime. If I have downtime, it is mostly caused by the hardware of the computers."
"Now, using this solution, it is much cheaper to have all of the data available for searching, not in real-time, but whenever there is a pending request."
"We use it for data science activities."
"Hortonworks should not be expensive at all to those looking into using it."
"My customers find the product cheaper compared to other solutions. The previous solution that we used did not have unified analytics like the runtime or the analog."
"HPE Ezmeral Data Fabric can be accessed from any namespace globally as you would access it from a machine using an NFS."
"It is a stable solution...It is a scalable solution."
"The model creation was very interesting, especially with the libraries provided by the platform."
"I like the administration part."
"The security of this solution could be improved. There should also be a way to basically have a blockchain enabled storage with the HDFS."
"There are better solutions out there that have more features than this one."
"The dashboard could be improved."
"While the deployed product is generally functional, there are instances where it presents difficulties."
"The Cloudera training has deteriorated significantly."
"The solution does not support multiple languages very well and this means users need to create work-arounds to implement some solutions."
"Currently, we are using many other tools such as Spark and Blade Job to improve the performance."
"The pricing needs to improve."
"Security and workload management need improvement."
"It's at end of life and no longer will there be improvements."
"More information could be there to simplify the process of running the product."
"Hive performance. If Hive performance increased, Hadoop would replace (not everywhere) traditional databases."
"The version control of the software is also an issue."
"It would also be nice if there were less coding involved."
"The cost of the solution is high and there is room for improvement."
"Deleting any service requires a lot of clean up, unlike Cloudera."
"The deployment could be faster. I want more support for the data lake in the next release."
"Having the ability to extend the services provided by the platform to an API architecture, a micro-services architecture, could be very helpful."
"HPE Ezmeral Data Fabric is not compatible with third-party tools."
"Upgrading Ezmeral to a new version is a pain. They're trying to make the solution more container-friendly, so I think they're going in the right direction. The only problem we've had in the past was the upgrades. The process isn't smooth due to how the Red Hat operating system upgrades currently work."
"The product is not user-friendly."
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