We performed a comparison between Hortonworks Data Platform 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 scalability is the key reason why we are on this platform."
"The product offers a fairly easy setup process."
"Hortonworks should not be expensive at all to those looking into using it."
"The data platform is pretty neat. The workflow is also really good."
"The upgrades and patches must come from Hortonworks."
"Ranger for security; with Ranger we can manager user’s permissions/access controls very easily."
"It is a scalable platform."
"We use it for data science activities."
"Overall the solution is excellent."
"The team members don't have to learn a new language and can implement complex tasks very easily using only SQL."
"It is a stable 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."
"Offers a variety of methods to design queries and incorporates the regular SQL syntax within tasks."
"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 solution is easy to understand if you have basic knowledge of SQL commands."
"I find the Thrift connection valuable."
"I work a lot with banking, IT and communications customers. Hortonworks must improve or must upgrade their services for these sectors."
"It would also be nice if there were less coding involved."
"I would like to see more support for containers such as Docker and OpenShift."
"The version control of the software is also an issue."
"The cost of the solution is high and there is room for improvement."
"More information could be there to simplify the process of running the product."
"Security and workload management need improvement."
"It's at end of life and no longer will there be improvements."
"There should be better integration with other solutions."
"This solution could be improved by adding monitoring and integration for the EMR."
"I've experienced some incompatibilities when using the Delta Lake format."
"There are many inconsistencies in syntax for the different querying tasks."
"In terms of improvement, the only thing that could be enhanced is the stability aspect of Spark SQL."
"It would be useful if Spark SQL integrated with some data visualization tools."
"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."
"Anything to improve the GUI would be helpful."
Hortonworks Data Platform is ranked 6th in Hadoop with 25 reviews while Spark SQL is ranked 4th in Hadoop with 14 reviews. Hortonworks Data Platform is rated 8.0, while Spark SQL is rated 7.8. The top reviewer of Hortonworks Data Platform writes "Good for secure containerization, and governance capabilities ". On the other hand, the top reviewer of Spark SQL writes "Offers the flexibility to handle large-scale data processing". Hortonworks Data Platform is most compared with Amazon EMR, Apache Spark, Cloudera DataFlow and HPE Ezmeral Data Fabric, whereas Spark SQL is most compared with Apache Spark, IBM Db2 Big SQL, Netezza Analytics, SAP HANA and HPE Ezmeral Data Fabric. See our Hortonworks Data Platform vs. Spark SQL report.
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