Netezza Performance Server (NPS) is an add-on data warehouse solution available on Cloud Pak for Data System platform, built over open source and optimized for High Performance Analytics with built-in hardware acceleration. Netezza Performance Server was previously named IBM Performance Server for PostgreSQL (IPS).
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IBM Watson Studio
Score 10.0 out of 10
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IBM Watson Studio enables users to build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio enables users can operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. The vendor states the solution simplifies AI lifecycle management and accelerates time to value with an open, flexible multicloud architecture.
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Pricing
IBM Netezza Performance Server
IBM Watson Studio on Cloud Pak for Data
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Pricing Offerings
IBM Netezza Performance Server
IBM Watson Studio
Free Trial
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Free/Freemium Version
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Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
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Community Pulse
IBM Netezza Performance Server
IBM Watson Studio on Cloud Pak for Data
Considered Both Products
IBM Netezza Performance Server
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IBM Watson Studio
Verified User
Consultant
Chose IBM Watson Studio on Cloud Pak for Data
AWS stacks up very favourably against Watson Studio, and in fact this is what the customer ultimately chose over Watson Studio after an evaluation period due to the sophistication, maturity, security, and capabilities of the AWS components. The downsides of AWS are having to …
We can query the data source and treat multiple databases as one with IBM Netezza Performance Server.
While delivering fast and reliable analytical performance, the IBM Netezza Performance Server requires minimal configuration and ongoing management.
To drive organizational performance, Netezza Performance Server automatically simplifies data and AI to centralize all analytics activities on the device, exactly where the data resides.
For data processing and application dashboards, IBM Netezza Performance Server is quite beneficial.
IBM Netezza Performance Server simplifies event setup by notifying you when a hardware component fails, allowing you to quickly replace it.
It has a lot of features that are good for teams working on large-scale projects and continuously developing and reiterating their data project models. Really helpful when dealing with large data. It is a kind of one-stop solution for all data science tasks like visualization, cleaning, analyzing data, and developing models but small teams might find a lot of features unuseful.
I received answers mostly at once and got answered even further my question: they gave me interesting points of view and suggestion for deepening in the learning path
Netezza is sufficient against similar products. It comes down to personal preference, I'd love to have the data objects popping up as I type but some people may not like it.
The main reason I personally changed over from Azure ML Studio is because it lacked any support for significant custom modelling with packages and services such as TensorFlow, scikit-learn, Microsoft Cognitive Toolkit and Spark ML. IBM Watson Studio provides these services and does so in a well integrated and easy to use fashion making it a preferable service over the other services that I have personally used.