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."We use it for data science activities."
"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."
"It is a scalable platform."
"Distributed computing, secure containerization, and governance capabilities are the most valuable features."
"The upgrades and patches must come from Hortonworks."
"The scalability is the key reason why we are on this platform."
"Ranger for security; with Ranger we can manager user’s permissions/access controls very easily."
"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."
"Spark SQL's efficiency in managing distributed data and its simplicity in expressing complex operations make it an essential part of our data pipeline."
"Offers a variety of methods to design queries and incorporates the regular SQL syntax within tasks."
"The team members don't have to learn a new language and can implement complex tasks very easily using only SQL."
"The stability was fine. It behaved as expected."
"It is a stable solution."
"Overall the solution is excellent."
"One of Spark SQL's most beautiful features is running parallel queries to go through enormous data."
"The performance is one of the most important features. It has an API to process the data in a functional manner."
"Deleting any service requires a lot of clean up, unlike Cloudera."
"Hive performance. If Hive performance increased, Hadoop would replace (not everywhere) traditional databases."
"It's at end of life and no longer will there be improvements."
"Security and workload management need improvement."
"I would like to see more support for containers such as Docker and OpenShift."
"More information could be there to simplify the process of running the product."
"I work a lot with banking, IT and communications customers. Hortonworks must improve or must upgrade their services for these sectors."
"The version control of the software is also an issue."
"It would be useful if Spark SQL integrated with some data visualization tools."
"It takes a bit of time to get used to using this solution versus Pandas as it has a steep learning curve."
"The solution needs to include graphing capabilities. Including financial charts would help improve everything overall."
"In the next release, maybe the visualization of some command-line features could be added."
"SparkUI could have more advanced versions of the performance and the queries and all."
"It would be beneficial for aggregate functions to include a code block or toolbox that explains its calculations or supported conditional statements."
"There should be better integration with other solutions."
"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."
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, SAP HANA, HPE Ezmeral Data Fabric and Netezza Analytics. See our Hortonworks Data Platform vs. Spark SQL report.
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