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."The most valuable feature is the Fault Tolerance and easy binding with other processes like Machine Learning, graph analytics."
"DataFrame: Spark SQL gives the leverage to create applications more easily and with less coding effort."
"The memory processing engine is the solution's most valuable aspect. It processes everything extremely fast, and it's in the cluster itself. It acts as a memory engine and is very effective in processing data correctly."
"The deployment of the product is easy."
"The solution is very stable."
"I found the solution stable. We haven't had any problems with it."
"Now, when we're tackling sentiment analysis using NLP technologies, we deal with unstructured data—customer chats, feedback on promotions or demos, and even media like images, audio, and video files. For processing such data, we rely on PySpark. Beneath the surface, Spark functions as a compute engine with in-memory processing capabilities, enhancing performance through features like broadcasting and caching. It's become a crucial tool, widely adopted by 90% of companies for a decade or more."
"There's a lot of functionality."
"Data compression. It was relatively impressive. I think at some point we were getting 4:1 compression if not more."
"Speed contributes to large capacity."
"The need for administration involvement is quite limited on the solution."
"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."
"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."
"It would be beneficial to enhance Spark's capabilities by incorporating models that utilize features not traditionally present in its framework."
"This solution currently cannot support or distribute neural network related models, or deep learning related algorithms. We would like this functionality to be developed."
"They could improve the issues related to programming language for the platform."
"We've had problems using a Python process to try to access something in a large volume of data. It crashes if somebody gives me the wrong code because it cannot handle a large volume of data."
"The management tools could use improvement. Some of the debugging tools need some work as well. They need to be more descriptive."
"The migration of data between different versions could be improved."
"It should support more programming languages."
"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."
"The hardware has a risk of failure. They need to improve this."
"The solution could implement more reporting tools and networking utilities."
"Disaster recovery support. Because it was an appliance, and if you wanted to support disaster recovery, you needed to buy two."
"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."
"The most valuable features of this solution are robustness and support."
"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."
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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