We performed a comparison between Apache Spark and Netezza Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Cloudera, Apache, Amazon and others in Hadoop."Spark helps us reduce startup time for our customers and gives a very high ROI in the medium term."
"The most valuable feature of Apache Spark is its ease of use."
"I found the solution stable. We haven't had any problems with it."
"Features include machine learning, real time streaming, and data processing."
"The product is useful for analytics."
"Provides a lot of good documentation compared to other solutions."
"Apache Spark provides a very high-quality implementation of distributed data processing."
"The tool's most valuable feature is its speed and efficiency. It's much faster than other tools and excels in parallel data processing. Unlike tools like Python or JavaScript, which may struggle with parallel processing, it allows us to handle large volumes of data with more power easily."
"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 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 need for administration involvement is quite limited on the solution."
"Speed contributes to large capacity."
"For me, as an end-user, everything that I do on the solution is simple, clear, and understandable."
"The solution’s integration with other platforms should be improved."
"The setup I worked on was really complex."
"The logging for the observability platform could be better."
"Technical expertise from an engineer is required to deploy and run high-tech tools, like Informatica, on Apache Spark, making it an area where improvements are required to make the process easier for users."
"I would like to see integration with data science platforms to optimize the processing capability for these tasks."
"We use big data manager but we cannot use it as conditional data so whenever we're trying to fetch the data, it takes a bit of time."
"When you first start using this solution, it is common to run into memory errors when you are dealing with large amounts of data."
"The solution needs to optimize shuffling between workers."
"The Analytics feature should be simplified."
"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 solution could implement more reporting tools and networking utilities."
"I'm not sure of IBM's roadmap currently, as the solution is coming up on its end of life."
"The hardware has a risk of failure. They need to improve this."
"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."
Apache Spark is ranked 2nd in Hadoop with 58 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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