In my current organization, we mainly use IBM Netezza Performance Server to integrate server, analytics and database in one single spot to gain real-time insights.
Pros
Has a simple infrastructure: Do not require tuning nor indexing.
Advanced security via self-encryption.
Unify data warehousing and BI with advanced analytics.
Cons
All the issues that I used to experience were all rectified by the vendor success team for free.
Likelihood to Recommend
IBM Netezza Performance Server best suits all needs encompassed in data analysis by consolidating all activities in one single system where data is hosted.
With data volumes scalable to petabytes, IBM Netezza Performance Server enables data insights and machine learning. Integrating a database, server, storage, and analytics into a single system with petabyte scalability is invaluable. IBM Netezza Performance Server is a high-performance, massively parallel system for extracting insights and performing analysis on large volumes of data. The event configuration option in the IBM Netezza Performance Server is important to provide notification of any hardware component failure for quick replacement.
Pros
IBM Netezza Performance Server enables capabilities to integrate with leading ETL solutions.
Data can be exported from the IBM Netezza Performance Server to a variety of formats, including Excel.
We can prioritize specific users and queries using IBM Netezza Performance Server.
Cons
After using the program, the hosting and productivity aspects of the IBM Netezza Performance Server are relatively lacking.
The IBM Netezza Performance Server membership fee is quite high.
Likelihood to Recommend
Netezza Performance Server enhances the data scientist's ability to rapidly design, train, and deploy machine learning models in the database. Netezza Performance Server is essential for implementing cognitive machine learning, providing data scientists with in-database analytics, and enabling them to collaborate on a single platform. Netezza Performance Server supports the use of built-in Spark as well as Python and R for rapid and sophisticated data science and machine learning adoption at scale.
We used this tool in managing our POS application on individual devices. We used it for multipurpose as well as data warehouse purposes too. 1:16 ratio between server and individual devices for point of sale applications. The transaction extraction process has been made so easier with this tool and sync is almost real-time. The product addresses different platforms such as hardwired devices and portable mobile devices also.
Pros
The speed of operations is really second to none
The data control aspect is really effective and very useful
Stability and no latency issues notices during operations
Cons
More tech support may make it easier as it is only limited to be done via company representatives
Overhead cost for replacements and services looks like it is high compared to others
Integration with other cloud based application will be great
Likelihood to Recommend
Flexibility to use simultaneous databases at the same time is great for transaction load and extractions. Analysis of reports makes it easier via this tool. Developing just the partition process makes it easier for the rest of the requirements out from this tool. It is easy to use with a user-friendly interface, integration with legacy operating system Linux is a great combination.
