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Compare Azure Virtual Machines and IBM Cloud Pak for Data 
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At a Glance
Market Segments
Enterprise (34.5% of reviews)
Enterprise (50.0% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Azure Virtual Machines
Star Rating
(385)4.4 out of 5
Market Segments
Enterprise (34.5% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about Azure Virtual MachinesIBM Cloud Pak for Data
Star Rating
(88)4.3 out of 5
Market Segments
Enterprise (50.0% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about IBM Cloud Pak for DataSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Azure Virtual Machines excels in "Ease of Setup" with a score of 8.6, making it a preferred choice for those who prioritize quick deployment. In contrast, IBM Cloud Pak for Data has a lower score of 7.2, indicating a more complex setup process that may require additional time and resources.
- Reviewers mention that Azure Virtual Machines offers superior "Scalability" with a score of 8.6, allowing businesses to easily adjust resources as needed. On the other hand, IBM Cloud Pak for Data scores 8.9 in "Scalability," but users note that its scalability is more tailored towards data analytics rather than general infrastructure needs.
- G2 users highlight Azure Virtual Machines' "Quality of Support" with a score of 8.5, indicating a strong customer service experience. Conversely, IBM Cloud Pak for Data has a slightly lower score of 8.3, with some users expressing concerns about response times and the depth of support provided.
- Users on G2 report that Azure Virtual Machines shines in "Customization" with a score of 8.0, allowing for tailored virtual machine configurations. In contrast, IBM Cloud Pak for Data lacks in this area, with users noting limited customization options for their data management needs.
- Reviewers mention that Azure Virtual Machines provides excellent "Data Recovery" capabilities, scoring 9.0, which is crucial for businesses concerned about data loss. IBM Cloud Pak for Data, while strong in data analytics, does not emphasize data recovery to the same extent, leading to a lower user satisfaction in this area.
- Users say that Azure Virtual Machines offers a more flexible "Pay by Usage" model with a score of 9.0, making it cost-effective for businesses with fluctuating workloads. In contrast, IBM Cloud Pak for Data's score of 8.6 suggests that its pricing structure may not be as adaptable, potentially leading to higher costs for users with variable usage patterns.
Pricing
Entry-Level Pricing
Azure Virtual Machines
No pricing availableIBM Cloud Pak for Data
No pricing availableFree Trial
Azure Virtual Machines
No trial information availableIBM Cloud Pak for Data
No trial information availableRatings
Meets Requirements
9.0
332
8.5
47
Ease of Use
8.6
332
8.1
47
Ease of Setup
8.6
198
7.2
26
Ease of Admin
8.6
190
7.6
27
Quality of Support
8.3
320
8.3
42
Has the product been a good partner in doing business?
8.9
182
8.1
25
Product Direction (% positive)
9.2
320
8.8
47
Features by Category
Customization
Not enough data
8.0
5
Not enough data
Not enough data
Not enough data
Not enough data
Infrastructure
Not enough data
Not enough data
Not enough data
9.0
5
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Infrastructure Provision
9.0
60
7.7
8
8.6
55
8.1
7
9.0
52
7.9
7
7.2
48
8.3
6
8.3
53
8.5
8
9.3
58
7.9
8
8.5
48
8.3
8
9.1
56
8.3
7
Management
8.9
55
8.6
7
8.9
53
8.3
7
8.7
54
8.1
8
Functionality
8.8
53
8.3
8
System
Not enough data
9.5
11
Model Development
Not enough data
8.3
8
Not enough data
8.5
8
Not enough data
9.1
9
Not enough data
8.8
8
Model Development
Not enough data
8.5
12
Machine/Deep Learning Services
Not enough data
8.7
9
Not enough data
9.4
8
Not enough data
9.6
8
Not enough data
9.0
7
Machine/Deep Learning Services
Not enough data
9.2
8
Not enough data
9.3
7
Deployment
Not enough data
9.3
9
Not enough data
9.3
9
Not enough data
8.9
9
Generative AI
Not enough data
8.3
5
Not enough data
8.3
5
Not enough data
8.3
5
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Data Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
8.3
5
Analytics
Not enough data
Not enough data
Security
Not enough data
9.0
5
Not enough data
Not enough data
Not enough data
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - Data Fabric
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Performance
8.4
25
Not enough data
8.3
25
Not enough data
9.0
26
Not enough data
Functionality
8.9
29
Not enough data
8.5
28
Not enough data
8.7
28
Not enough data
9.3
29
Not enough data
Agentic AI - Server Virtualization
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Scalability and Performance - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Cost and Efficiency - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Integration and Extensibility - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Security and Compliance - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Usability and Support - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Statistical Tool
Not enough data
8.3
5
Not enough data
8.8
8
Not enough data
8.6
7
Data Analysis
Not enough data
8.7
9
Not enough data
9.0
7
Decision Making
Not enough data
8.3
6
Not enough data
8.8
7
Not enough data
8.8
8
Not enough data
8.3
8
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Data Transformation
Not enough data
8.5
27
|
Verified
Not enough data
9.1
15
|
Verified
Connectivity
Not enough data
8.0
23
|
Verified
Not enough data
8.6
22
|
Verified
Not enough data
8.1
25
|
Verified
Not enough data
8.7
24
|
Verified
Operations
Not enough data
8.7
26
|
Verified
Not enough data
8.9
25
|
Verified
Not enough data
8.4
23
|
Verified
Not enough data
8.8
24
|
Verified
Not enough data
8.7
13
|
Verified
Building Reports
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Platform
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
Azure Virtual Machines and IBM Cloud Pak for Data are categorized as Infrastructure as a Service (IaaS)
Unique Categories
Azure Virtual Machines is categorized as Server Virtualization
IBM Cloud Pak for Data is categorized as Data Fabric, Virtual Private Cloud (VPC), Big Data Analytics, Data Science and Machine Learning Platforms, Predictive Analytics, and Generative AI Infrastructure
Reviews
Reviewers' Company Size
Azure Virtual Machines
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
IBM Cloud Pak for Data
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Small-Business
(50 or fewer emp.)
Mid-Market
(51-1000 emp.)
Enterprise
(> 1000 emp.)
Reviewers' Industry
Information Technology and Services
29.8%
Computer Software
18.2%
Computer & Network Security
7.3%
Accounting
4.3%
Information Services
2.4%
Other
37.9%
Computer Software
12.9%
Information Technology and Services
8.6%
Banking
8.6%
Financial Services
5.7%
Education Management
5.7%
Other
58.6%
Alternatives
Discussions
What are Azure virtual machines used for?
2 Comments
RL
Some use cases:
Application Hosting, Development and Testing, Data Processing and Analytics, Disaster Recovery, High-Performance Computing (HPC), Hybrid...Read more
IBM Cloud Pak for Data has no discussions with answers
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