We performed a comparison between HPE Ezmeral Data Fabric and Spark SQL 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 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."
"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."
"I like the administration part."
"It is a stable solution...It is a scalable solution."
"Certain data sets that are very large are very difficult to process with Pandas and Python libraries. Spark SQL has helped us a lot with that."
"It is a stable solution."
"I find the Thrift connection valuable."
"The team members don't have to learn a new language and can implement complex tasks very easily using only SQL."
"One of Spark SQL's most beautiful features is running parallel queries to go through enormous data."
"Offers a variety of methods to design queries and incorporates the regular SQL syntax within tasks."
"The speed of getting data."
"Spark SQL's efficiency in managing distributed data and its simplicity in expressing complex operations make it an essential part of our data pipeline."
"The product is not user-friendly."
"HPE Ezmeral Data Fabric is not compatible with third-party tools."
"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."
"The deployment could be faster. I want more support for the data lake in the next release."
"There are many inconsistencies in syntax for the different querying tasks."
"The solution needs to include graphing capabilities. Including financial charts would help improve everything overall."
"In terms of improvement, the only thing that could be enhanced is the stability aspect of Spark SQL."
"Being a new user, I am not able to find out how to partition it correctly. I probably need more information or knowledge. In other database solutions, you can easily optimize all partitions. I haven't found a quicker way to do that in Spark SQL. It would be good if you don't need a partition here, and the system automatically partitions in the best way. They can also provide more educational resources for new users."
"In the next release, maybe the visualization of some command-line features could be added."
"I've experienced some incompatibilities when using the Delta Lake format."
"It takes a bit of time to get used to using this solution versus Pandas as it has a steep learning curve."
"This solution could be improved by adding monitoring and integration for the EMR."
HPE Ezmeral Data Fabric is ranked 5th in Hadoop with 12 reviews while Spark SQL is ranked 4th in Hadoop with 14 reviews. HPE Ezmeral Data Fabric is rated 8.0, while Spark SQL is rated 7.8. The top reviewer of HPE Ezmeral Data Fabric writes "It's flexible and easily accessible across multiple locations, but the upgrade process is complicated". On the other hand, the top reviewer of Spark SQL writes "Offers the flexibility to handle large-scale data processing". HPE Ezmeral Data Fabric is most compared with Cloudera Distribution for Hadoop, Amazon EMR, IBM Spectrum Computing, MongoDB and Hortonworks Data Platform, whereas Spark SQL is most compared with Apache Spark, IBM Db2 Big SQL, SAP HANA and Netezza Analytics. See our HPE Ezmeral Data Fabric vs. Spark SQL report.
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