Google Cloud Platform is a suite of cloud computing services used to build apps or take advantage of cloud infrastructural services, achieve legacy infrastructure modernization, or manage enterprise data and analytic needs.
$0
(25+ apps are currently available at no cost)
IBM Power Virtual Server
Score 9.2 out of 10
N/A
IBM presents their Power Systems Virtual Server as a scalable, cost-effective way to run IBM AIX, IBM i and Linux workloads.
They both have their own ups and downs and it totally depends on the team which suits them best. IBM Power Virtual Server has Performance, Scalability, Reliability and Availability, Compatibility, and Good Vendor Support. The specific use case and workload requirements played a …
When most of our stuff is in Google Cloud Platform, it works great to integrate and cross/share data that is all in Google Cloud Platform or BigQuery. It has simplified things from a permissions perspective as well. I'd say it is less appropriate when trying to test something quickly locally, or when half your stuff is in AWS or another provider.
It is really impactful in terms of scenarios like ERP systems and Data Analytics where heavy data needs to be analysed in terms of volume and their needs to be high scalability offering so in that scenario it is a great asset and features like distribution of workload using AI capabilities by leveraging modern IBM offerings like Watson is really helpful the area in which it could improve is native development of application in terms of adoption of New cloud Technologies
The UI is so confusing. The console is good, but it is like a maze. There are too many menus and settings, and things do not work as expected. It takes time to get friendly, and it is not friendly for new users.
Support experience: Sometimes, you get a great engineer, but other times, it's very difficult to talk with them as they are unable to respond as expected and solve issues late.
Region and zone are issues, as not all services are available in all regions, which is lacking when deploying something in the same region or zone.
At the moment we are 100% satisfied with the performance and our support team is well used to the process involved. So unless we have some major issues in adopting, we are sure to be with IBM itself.
The Google Cloud Platform console is pretty slick for BigQuery especially. I have liked the visibility I get from using that and the way to integrate and see what's in our data lake. The logging console for tracking GKE jobs isn't quite as great, which is why it doesn't get a full 10.
I would rate IBM Power Virtual Server’s overall usability as an 8 out of 10. The platform offers a solid interface and intuitive dashboard, making it relatively easy for users with cloud experience to navigate. Its scalability and flexibility are strong points. However, the learning curve for new users can be steep, especially when dealing with complex integrations or configurations. While documentation and support are extensive, some users may find the setup process challenging. Overall, it’s highly functional but could be streamlined further for beginners.
As with most IBM products the ongoing support for IBM Power Virtual Server is solid and consistent. IBM provides a clear roadmap for receiving support of their products. Both voice and online response is offered. It is obvious that IBM has the internal systems and culture to maintain support functions. This starts from the initial support call to the problem analysis and continues through the problem resolution. Documentation and communication are consistent within this process.
Google Cloud Platform is release later than Amazon web service, I think that why Google Cloud Platform can learned and optimized the Dashboard and some features that make it easy to use and can be cheaper than amazon web service.
They both have their own ups and downs and it totally depends on the team which suits them best. IBM Power Virtual Server has Performance, Scalability, Reliability and Availability, Compatibility, and Good Vendor Support. The specific use case and workload requirements played a significant role. Some workloads may benefit from IBM Power Systems' architecture, while others may perform equally well on alternative platforms.
I would rate IBM Cognos Analytics’ scalability as a 9 out of 10. The platform is highly capable of handling large volumes of data and supporting thousands of users with ease. Its architecture is designed for high performance, though it may require fine-tuning for extremely complex data environments to maintain optimal performance.
It allows us to focus our efforts on other, more important items at hand
It gives us an affordable option letting me know it's available to all users, not just the largest scale ones out there
The customer service is always helpful and reliable, along with the service itself which lets me focus on my work instead of worrying about the service.
There have also been 80% fewer application crashes due to a lack of resources that previously ran on the X86 platform.
Administration management has been simplified and staff can dedicate themselves to the development of applications, instead of providing support to users when the applications do not respond efficiently, this made staff 45% more productive.
