We performed a comparison between Apache Spark and HPE Ezmeral Data Fabric based on real PeerSpot user reviews.
Find out in this report how the two Hadoop solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The solution is scalable."
"Apache Spark can do large volume interactive data analysis."
"The data processing framework is good."
"I feel the streaming is its best feature."
"The product’s most valuable features are lazy evaluation and workload distribution."
"DataFrame: Spark SQL gives the leverage to create applications more easily and with less coding effort."
"Apache Spark provides a very high-quality implementation of distributed data processing."
"The memory processing engine is the solution's most valuable aspect. It processes everything extremely fast, and it's in the cluster itself. It acts as a memory engine and is very effective in processing data correctly."
"The model creation was very interesting, especially with the libraries provided by the platform."
"I like the administration part."
"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 setup I worked on was really complex."
"When you want to extract data from your HDFS and other sources then it is kind of tricky because you have to connect with those sources."
"There could be enhancements in optimization techniques, as there are some limitations in this area that could be addressed to further refine Spark's performance."
"It needs a new interface and a better way to get some data. In terms of writing our scripts, some processes could be faster."
"If you have a Spark session in the background, sometimes it's very hard to kill these sessions because of D allocation."
"More ML based algorithms should be added to it, to make it algorithmic-rich for developers."
"The solution needs to optimize shuffling between workers."
"It requires overcoming a significant learning curve due to its robust and feature-rich nature."
"The product is not user-friendly."
"HPE Ezmeral Data Fabric is not compatible with third-party tools."
"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."
"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."
Apache Spark is ranked 1st in Hadoop with 60 reviews while HPE Ezmeral Data Fabric is ranked 5th in Hadoop with 12 reviews. Apache Spark is rated 8.4, while HPE Ezmeral Data Fabric is rated 8.0. The top reviewer of Apache Spark writes "Reliable, able to expand, and handle large amounts of data well". On the other hand, the top reviewer of HPE Ezmeral Data Fabric writes "It's flexible and easily accessible across multiple locations, but the upgrade process is complicated". Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and Cloudera Distribution for Hadoop, whereas HPE Ezmeral Data Fabric is most compared with Cloudera Distribution for Hadoop, Amazon EMR, IBM Spectrum Computing, MongoDB and BlueData. See our Apache Spark vs. HPE Ezmeral Data Fabric report.
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