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 product’s most valuable feature is the SQL tool. It enables us to create a database and publish it."
"The main feature that we find valuable is that it is very fast."
"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 solution has been very stable."
"I like that it can handle multiple tasks parallelly. I also like the automation feature. JavaScript also helps with the parallel streaming of the library."
"The solution is very stable."
"I appreciate everything about the solution, not just one or two specific features. The solution is highly stable. I rate it a perfect ten. The solution is highly scalable. I rate it a perfect ten. The initial setup was straightforward. I recommend using the solution. Overall, I rate the solution a perfect ten."
"AI libraries are the most valuable. They provide extensibility and usability. Spark has a lot of connectors, which is a very important and useful feature for AI. You need to connect a lot of points for AI, and you have to get data from those systems. Connectors are very wide in Spark. With a Spark cluster, you can get fast results, especially for AI."
"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."
"It is a stable solution...It is a scalable solution."
"I like the administration part."
"The model creation was very interesting, especially with the libraries provided by the platform."
"HPE Ezmeral Data Fabric can be accessed from any namespace globally as you would access it from a machine using an NFS."
"Apache Spark provides very good performance The tuning phase is still tricky."
"The migration of data between different versions could be improved."
"We are building our own queries on Spark, and it can be improved in terms of query handling."
"One limitation is that not all machine learning libraries and models support it."
"I would like to see integration with data science platforms to optimize the processing capability for these tasks."
"In data analysis, you need to take real-time data from different data sources. You need to process this in a subsecond, do the transformation in a subsecond, and all that."
"The management tools could use improvement. Some of the debugging tools need some work as well. They need to be more descriptive."
"The solution needs to optimize shuffling between workers."
"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 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."
"The product is not user-friendly."
"HPE Ezmeral Data Fabric is not compatible with third-party tools."
Apache Spark is ranked 2nd in Hadoop with 58 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, MongoDB, IBM Spectrum Computing and BlueData. See our Apache Spark vs. HPE Ezmeral Data Fabric report.
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