We performed a comparison between Apache Spark and Hortonworks Data Platform 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."It is useful for handling large amounts of data. It is very useful for scientific purposes."
"The most valuable feature of Apache Spark is its ease of use."
"One of the key features is that Apache Spark is a distributed computing framework. You can help multiple slaves and distribute the workload between them."
"The solution has been very stable."
"Apache Spark can do large volume interactive data analysis."
"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."
"Spark helps us reduce startup time for our customers and gives a very high ROI in the medium term."
"It's easy to prepare parallelism in Spark, run the solution with specific parameters, and get good performance."
"We use it for data science activities."
"The product offers a fairly easy setup process."
"Distributed computing, secure containerization, and governance capabilities are the most valuable features."
"Ranger for security; with Ranger we can manager user’s permissions/access controls very easily."
"The scalability is the key reason why we are on this platform."
"Ambari Web UI: user-friendly."
"The upgrades and patches must come from Hortonworks."
"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."
"When you want to extract data from your HDFS and other sources then it is kind of tricky because you have to connect with those sources."
"Apart from the restrictions that come with its in-memory implementation. It has been improved significantly up to version 3.0, which is currently in use."
"Apache Spark is very difficult to use. It would require a data engineer. It is not available for every engineer today because they need to understand the different concepts of Spark, which is very, very difficult and it is not easy to learn."
"The solution needs to optimize shuffling between workers."
"We are building our own queries on Spark, and it can be improved in terms of query handling."
"They could improve the issues related to programming language for the platform."
"Include more machine learning algorithms and the ability to handle streaming of data versus micro batch processing."
"The graphical user interface (UI) could be a bit more clear. It's very hard to figure out the execution logs and understand how long it takes to send everything. If an execution is lost, it's not so easy to understand why or where it went. I have to manually drill down on the data processes which takes a lot of time. Maybe there could be like a metrics monitor, or maybe the whole log analysis could be improved to make it easier to understand and navigate."
"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."
"I work a lot with banking, IT and communications customers. Hortonworks must improve or must upgrade their services for these sectors."
"Security and workload management need improvement."
"It's at end of life and no longer will there be improvements."
"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."
"Hive performance. If Hive performance increased, Hadoop would replace (not everywhere) traditional databases."
"The cost of the solution is high and there is room for improvement."
Apache Spark is ranked 1st in Hadoop with 60 reviews while Hortonworks Data Platform is ranked 6th in Hadoop with 25 reviews. Apache Spark is rated 8.4, while Hortonworks Data Platform 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 Hortonworks Data Platform writes "Good for secure containerization, and governance capabilities ". Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and Cloudera Distribution for Hadoop, whereas Hortonworks Data Platform is most compared with Amazon EMR, Cloudera DataFlow and HPE Ezmeral Data Fabric. See our Apache Spark vs. Hortonworks Data Platform report.
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