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."Ambari Web UI: user-friendly."
"The data platform is pretty neat. The workflow is also really good."
"It is a scalable platform."
"Hortonworks should not be expensive at all to those looking into using it."
"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."
"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."
"Ranger for security; with Ranger we can manager user’s permissions/access controls very easily."
"The upgrades and patches must come from Hortonworks."
"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 speed of getting data."
"The team members don't have to learn a new language and can implement complex tasks very easily using only SQL."
"The performance is one of the most important features. It has an API to process the data in a functional manner."
"This solution is useful to leverage within a distributed ecosystem."
"Overall the solution is excellent."
"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."
"More information could be there to simplify the process of running the product."
"Hive performance. If Hive performance increased, Hadoop would replace (not everywhere) traditional databases."
"Security and workload management need improvement."
"The cost of the solution is high and there is room for improvement."
"Since Cloudera acquired HDP, it's been bundled with CBH and HDP. However, the biggest challenge is cloud storage integration with Azure, GCP, and AWS."
"I would like to see more support for containers such as Docker and OpenShift."
"The version control of the software is also an issue."
"Deleting any service requires a lot of clean up, unlike Cloudera."
"In terms of improvement, the only thing that could be enhanced is the stability aspect of Spark SQL."
"I've experienced some incompatibilities when using the Delta Lake format."
"The solution needs to include graphing capabilities. Including financial charts would help improve everything overall."
"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."
"There should be better integration with other solutions."
"In the next update, we'd like to see better performance for small points of data. It is possible but there are better tools that are faster and cheaper."
"SparkUI could have more advanced versions of the performance and the queries and all."
"It takes a bit of time to get used to using this solution versus Pandas as it has a steep learning curve."
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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