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Compare AWS Bedrock and IBM Cloud Pak for Data 
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At a Glance
Market Segments
Enterprise (38.6% of reviews)
Enterprise (50.0% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
AWS Bedrock
Star Rating
(44)4.4 out of 5
Market Segments
Enterprise (38.6% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about AWS BedrockIBM 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 IBM Cloud Pak for Data offers robust data governance features, which are essential for enterprises managing sensitive information, while AWS Bedrock is praised for its seamless integration with other AWS services, making it easier for users already within the AWS ecosystem.
- Reviewers mention that the ease of setup for AWS Bedrock is significantly higher, with a score of 8.5 compared to IBM Cloud Pak for Data's 7.2, indicating that users find AWS Bedrock more straightforward to implement in their existing workflows.
- G2 users highlight that IBM Cloud Pak for Data excels in providing comprehensive analytics capabilities, but AWS Bedrock shines in its user-friendly interface, reflected in its higher ease of use score of 8.4 versus IBM's 8.1.
- Users on G2 report that the quality of support for AWS Bedrock is superior, with a score of 8.6, as compared to IBM Cloud Pak for Data's 8.3, suggesting that AWS provides more responsive and helpful customer service.
- Reviewers say that while both products are strong contenders in the enterprise market, AWS Bedrock has a slight edge in product direction with a score of 9.6, indicating a more positive outlook on future developments compared to IBM's 8.8.
- Users mention that IBM Cloud Pak for Data is particularly beneficial for organizations focused on data compliance and security, while AWS Bedrock is favored for its innovative features like AI model deployment, which users find enhances their operational efficiency.
Pricing
Entry-Level Pricing
AWS Bedrock
No pricing availableIBM Cloud Pak for Data
No pricing availableFree Trial
AWS Bedrock
No trial information availableIBM Cloud Pak for Data
No trial information availableRatings
Meets Requirements
8.6
44
8.5
47
Ease of Use
8.1
44
8.1
47
Ease of Setup
8.4
43
7.2
26
Ease of Admin
9.0
15
7.6
27
Quality of Support
8.5
43
8.3
42
Has the product been a good partner in doing business?
8.5
14
8.1
25
Product Direction (% positive)
9.5
43
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
Not enough data
7.7
8
Not enough data
8.1
7
Not enough data
7.9
7
Not enough data
8.3
6
Not enough data
8.5
8
Not enough data
7.9
8
Not enough data
8.3
8
Not enough data
8.3
7
Management
Not enough data
8.6
7
Not enough data
8.3
7
Not enough data
8.1
8
Functionality
Not enough data
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
Scalability and Performance - Generative AI Infrastructure
8.9
14
Not enough data
8.5
13
Not enough data
8.2
14
Not enough data
Cost and Efficiency - Generative AI Infrastructure
8.1
14
Not enough data
8.5
14
Not enough data
7.9
14
Not enough data
Integration and Extensibility - Generative AI Infrastructure
8.6
14
Not enough data
8.8
14
Not enough data
8.2
14
Not enough data
Security and Compliance - Generative AI Infrastructure
8.6
14
Not enough data
8.7
14
Not enough data
8.5
14
Not enough data
Usability and Support - Generative AI Infrastructure
7.7
14
Not enough data
7.7
14
Not enough data
Prompt Engineering - Large Language Model Operationalization (LLMOps)
8.0
5
Not enough data
7.3
5
Not enough data
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Model Garden - Large Language Model Operationalization (LLMOps)
8.7
5
Not enough data
Custom Training - Large Language Model Operationalization (LLMOps)
7.7
5
Not enough data
Application Development - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Model Deployment - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
8.3
5
Not enough data
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Model Monitoring - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Security - Large Language Model Operationalization (LLMOps)
9.0
5
Not enough data
Not enough data
Not enough data
Gateways & Routers - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Customization - AI Agent Builders
7.9
7
Not enough data
7.6
7
Not enough data
7.7
8
Not enough data
Functionality - AI Agent Builders
7.5
8
Not enough data
7.4
7
Not enough data
7.4
7
Not enough data
8.1
7
Not enough data
Data and Analytics - AI Agent Builders
8.1
7
Not enough data
8.1
7
Not enough data
9.3
7
Not enough data
Integration - AI Agent Builders
8.3
7
Not enough data
8.3
7
Not enough data
7.9
7
Not enough data
7.5
6
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
AWS Bedrock and IBM Cloud Pak for Data are categorized as Generative AI Infrastructure
Unique Categories
AWS Bedrock is categorized as Large Language Model Operationalization (LLMOps) and AI Agent Builders
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 Infrastructure as a Service (IaaS)
Reviews
Reviewers' Company Size
AWS Bedrock
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
22.7%
Computer Software
18.2%
Financial Services
6.8%
Consulting
4.5%
Retail
4.5%
Other
43.2%
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
AWS Bedrock has no discussions with answers
IBM Cloud Pak for Data has no discussions with answers
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