We performed a comparison between Apache Spark and Netezza Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop."Apache Spark provides a very high-quality implementation of distributed data processing."
"The distribution of tasks, like the seamless map-reduce functionality, is quite impressive."
"Its scalability and speed are very valuable. You can scale it a lot. It is a great technology for big data. It is definitely better than a lot of earlier warehouse or pipeline solutions, such as Informatica. Spark SQL is very compliant with normal SQL that we have been using over the years. This makes it easy to code in Spark. It is just like using normal SQL. You can use the APIs of Spark or you can directly write SQL code and run it. This is something that I feel is useful in Spark."
"The most valuable feature of Apache Spark is its memory processing because it processes data over RAM rather than disk, which is much more efficient and fast."
"The solution is scalable."
"The deployment of the product is easy."
"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."
"The most valuable feature is the Fault Tolerance and easy binding with other processes like Machine Learning, graph analytics."
"The need for administration involvement is quite limited on 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."
"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."
"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."
"The most valuable feature is the performance."
"Data compression. It was relatively impressive. I think at some point we were getting 4:1 compression if not more."
"The management tools could use improvement. Some of the debugging tools need some work as well. They need to be more descriptive."
"This solution currently cannot support or distribute neural network related models, or deep learning related algorithms. We would like this functionality to be developed."
"In data analysis, you need to take real-time data from different data sources. You need to process this in a subsecond, do the transformation in a subsecond, and all that."
"The solution’s integration with other platforms should be improved."
"At times during the deployment process, the tool goes down, making it look less robust. To take care of the issues in the deployment process, users need to do manual interventions occasionally."
"Include more machine learning algorithms and the ability to handle streaming of data versus micro batch processing."
"The solution must improve its performance."
"At the initial stage, the product provides no container logs to check the activity."
"The most valuable features of this solution are robustness and support."
"Disaster recovery support. Because it was an appliance, and if you wanted to support disaster recovery, you needed to buy two."
"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."
"In-DB processing with SAS Analytics, since this is supposed to be an analytics server so the expectation is there."
"The hardware has a risk of failure. They need to improve this."
"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."
Apache Spark is ranked 1st in Hadoop with 60 reviews while Netezza Analytics is ranked 11th in Hadoop. Apache Spark is rated 8.4, while Netezza Analytics is rated 7.4. 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 Netezza Analytics writes "ARULES() function is the fastest implementation of the associations algorithm (a priori or tree) I have worked with". Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and Cloudera Distribution for Hadoop, whereas Netezza Analytics is most compared with Spark SQL and HPE Ezmeral Data Fabric.
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