Amazon Deep Learning AMIs vs. IBM Power Virtual Server

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon Deep Learning AMIs
Score 8.7 out of 10
N/A
AMIs are Amazon Machine Images, virtual appliance deployed on EC2. The AWS Deep Learning AMIs provide machine learning practitioners and researchers with the infrastructure and tools to accelerate deep learning in the cloud, at scale. Users can launch Amazon EC2 instances pre-installed with deep learning frameworks and interfaces such as TensorFlow, PyTorch, Apache MXNet, Chainer, Gluon, Horovod, and Keras to train sophisticated, custom AI models, experiment with new algorithms, or to learn new…N/A
IBM Power Virtual Server
Score 8.2 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​.N/A
Pricing
Amazon Deep Learning AMIsIBM Power Virtual Server
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Amazon Deep Learning AMIsIBM Power Virtual Server
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeOptional
Additional Details
More Pricing Information
Community Pulse
Amazon Deep Learning AMIsIBM Power Virtual Server
Top Pros
Top Cons
Features
Amazon Deep Learning AMIsIBM Power Virtual Server
Infrastructure-as-a-Service (IaaS)
Comparison of Infrastructure-as-a-Service (IaaS) features of Product A and Product B
Amazon Deep Learning AMIs
-
Ratings
IBM Power Virtual Server
8.3
186 Ratings
2% above category average
Service-level Agreement (SLA) uptime00 Ratings8.7185 Ratings
Dynamic scaling00 Ratings8.2184 Ratings
Elastic load balancing00 Ratings8.2181 Ratings
Pre-configured templates00 Ratings7.7180 Ratings
Monitoring tools00 Ratings9.0183 Ratings
Pre-defined machine images00 Ratings8.4181 Ratings
Operating system support00 Ratings8.2183 Ratings
Security controls00 Ratings8.6182 Ratings
Automation00 Ratings7.6159 Ratings
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Amazon Deep Learning AMIsIBM Power Virtual Server
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Score 8.9 out of 10
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Score 9.3 out of 10
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User Ratings
Amazon Deep Learning AMIsIBM Power Virtual Server
Likelihood to Recommend
10.0
(2 ratings)
8.4
(186 ratings)
Likelihood to Renew
-
(0 ratings)
9.6
(4 ratings)
Usability
-
(0 ratings)
2.0
(3 ratings)
Availability
-
(0 ratings)
7.0
(1 ratings)
Performance
-
(0 ratings)
8.0
(1 ratings)
Support Rating
-
(0 ratings)
8.1
(2 ratings)
Implementation Rating
-
(0 ratings)
7.0
(1 ratings)
Configurability
-
(0 ratings)
9.0
(1 ratings)
Ease of integration
-
(0 ratings)
8.0
(1 ratings)
Product Scalability
-
(0 ratings)
7.0
(1 ratings)
Vendor post-sale
-
(0 ratings)
8.0
(1 ratings)
Vendor pre-sale
-
(0 ratings)
8.0
(1 ratings)
User Testimonials
Amazon Deep Learning AMIsIBM Power Virtual Server
Likelihood to Recommend
Amazon AWS
Amazon AMIs has been very useful for the quick setup and implementation of deep learning for data analysis which is something I have used the service for in my own research. We commonly use the service to enable students to run intensive deep learning algorithms for their assessments. This service works well in this scenario as it allows students to quickly set up a suitable environment and get started with little hassle. If you are looking to run simple, surface level deep learning algorithms (kind of contradictory statement I know) then AMI is more complicated than most will need. When it comes to teaching the basics of Machine Learning, this kind of system is unnecessary and there are other alternatives which can be used. That being said this service is a must if you are looking to run complex deep learning via the cloud.
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IBM
Due to its reliability, it is well-suited for mission-critical applications. It is also well suited for running multiple applications on a single server and fully utilizing the server's full capacity. However, it is not well suited for servers that require dedicated IO resources.
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Pros
Amazon AWS
  • Setting up environment
  • Support for different types of machines
  • Perfect for Machine Learning / Deep Learning use cases
  • Nvidia / Cuda / Conda support easily
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IBM
  • It is easy to segregate test environment with production environment
  • security and compliance
  • IBM server are scalable with - with increase in data it can dynamically allocate the resources with saves the company cost
  • it is very convenient to use with help of its hardware management console and integrated virtualization manager.
  • The best part it , it support our legacy system.
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Cons
Amazon AWS
  • Some aspects of the User Interface are quite confusing and activating packages can be a bit convoluted
  • It can be a bit confusing to switch between frameworks for novice users
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IBM
  • Having a wider selection of software to work with would be welcome.
  • Training and education is daunting at first and could be simplified.
  • Much of the automation is wonderful after it is set up but getting started has a steep learning curve.
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Likelihood to Renew
Amazon AWS
No answers on this topic
IBM
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.
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Usability
Amazon AWS
No answers on this topic
IBM
Power Systems Virtual Server on IBM Cloud for IBMi's overall usability is good, but it can be difficult for new users, some learning is needed, but there are tonns of online documentation.
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Reliability and Availability
Amazon AWS
No answers on this topic
IBM
Very easy to use.
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Performance
Amazon AWS
No answers on this topic
IBM
Easy to use.
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Support Rating
Amazon AWS
No answers on this topic
IBM
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.
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Implementation Rating
Amazon AWS
No answers on this topic
IBM
It is economic.
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Alternatives Considered
Amazon AWS
Both of these services provide similar functionality and from my experience both are top class services which cover most of your needs. I think ultimately it comes down to what you need each service for. For example Amazon DL AMIs allows for clustering by default meaning I am able to run several clustering algorithms without a problem whereas IBM Watson Studio doesn't provide this functionality. They both provide a wide range of default packages such as Amazon providing caffe-2 and IBM providing sci-kitlearn. My main point is that both are very good services which have very similar functionality, you just need to think about the costs, suitability of features and integration with other services you are using.
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IBM
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.
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Scalability
Amazon AWS
No answers on this topic
IBM
It is efficient.
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Return on Investment
Amazon AWS
  • Saves a lot of Infra Costs
  • Saves a lot of time in handling environment issues
  • Easy to start a new instance
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IBM
  • We have had a return on investment of 30%.
  • 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.
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ScreenShots