We performed a comparison between Netezza Analytics and Spark SQL based on real PeerSpot user reviews.
Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop."The most valuable feature is the performance."
"The need for administration involvement is quite limited on the solution."
"Data compression. It was relatively impressive. I think at some point we were getting 4:1 compression if not more."
"The performance of the solution is its most valuable feature. The solution is easy to administer as well. It's very user-friendly. On the technical side, the architecture is simple to understand and you don't need too many administrators to handle the solution."
"For me, as an end-user, everything that I do on the solution is simple, clear, and understandable."
"Speed contributes to large capacity."
"It is a back end for our SSIS, MicroStrategy,, Tableau. All of these are connecting to get the data. To do so we are also using our analytics which is built on the data."
"One of Spark SQL's most beautiful features is running parallel queries to go through enormous data."
"The speed of getting data."
"The solution is easy to understand if you have basic knowledge of SQL commands."
"This solution is useful to leverage within a distributed ecosystem."
"It is a stable solution."
"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."
"I find the Thrift connection valuable."
"The most valuable features of this solution are robustness and support."
"I'm not sure of IBM's roadmap currently, as the solution is coming up on its end of life."
"Administration of this product is too tough. It's very complex because of the tools which it's missing."
"This product is being discontinued from IBM, and I would like to have some kind of upgrade available."
"The hardware has a risk of failure. They need to improve this."
"Disaster recovery support. Because it was an appliance, and if you wanted to support disaster recovery, you needed to buy two."
"The Analytics feature should be simplified."
"The solution could implement more reporting tools and networking utilities."
"It takes a bit of time to get used to using this solution versus Pandas as it has a steep learning curve."
"There are many inconsistencies in syntax for the different querying tasks."
"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."
"This solution could be improved by adding monitoring and integration for the EMR."
"In terms of improvement, the only thing that could be enhanced is the stability aspect of Spark SQL."
"Anything to improve the GUI would be helpful."
"There should be better integration with other solutions."
Netezza Analytics is ranked 11th in Hadoop while Spark SQL is ranked 4th in Hadoop with 14 reviews. Netezza Analytics is rated 7.4, while Spark SQL is rated 7.8. The top reviewer of Netezza Analytics writes "ARULES() function is the fastest implementation of the associations algorithm (a priori or tree) I have worked with". On the other hand, the top reviewer of Spark SQL writes "Offers the flexibility to handle large-scale data processing". Netezza Analytics is most compared with HPE Ezmeral Data Fabric, whereas Spark SQL is most compared with Apache Spark, IBM Db2 Big SQL, HPE Ezmeral Data Fabric and SAP HANA.
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