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 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."
"Data compression. It was relatively impressive. I think at some point we were getting 4:1 compression if not more."
"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."
"For me, as an end-user, everything that I do on the solution is simple, clear, and understandable."
"Speed contributes to large capacity."
"The need for administration involvement is quite limited on the solution."
"The most valuable feature is the performance."
"It is a stable solution."
"Data validation and ease of use are the most valuable features."
"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."
"The speed of getting data."
"Offers a variety of methods to design queries and incorporates the regular SQL syntax within tasks."
"The stability was fine. It behaved as expected."
"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."
"The solution could implement more reporting tools and networking utilities."
"The hardware has a risk of failure. They need to improve this."
"The most valuable features of this solution are robustness and support."
"In-DB processing with SAS Analytics, since this is supposed to be an analytics server so the expectation is there."
"The Analytics feature should be simplified."
"I'm not sure of IBM's roadmap currently, as the solution is coming up on its end of life."
"This product is being discontinued from IBM, and I would like to have some kind of upgrade available."
"Administration of this product is too tough. It's very complex because of the tools which it's missing."
"In the next release, maybe the visualization of some command-line features could be added."
"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."
"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."
"I've experienced some incompatibilities when using the Delta Lake format."
"It would be useful if Spark SQL integrated with some data visualization tools."
"The solution needs to include graphing capabilities. Including financial charts would help improve everything overall."
"There are many inconsistencies in syntax for the different querying tasks."
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, SAP HANA and HPE Ezmeral Data Fabric.
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