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At a Glance
Market Segments
Small-Business (54.5% of reviews)
Enterprise (50.0% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
H2O
Star Rating
(24)4.5 out of 5
Market Segments
Small-Business (54.5% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about H2OIBM 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 H2O excels in Data Ingestion & Wrangling with a score of 8.5, while IBM Cloud Pak for Data shines even brighter with a score of 9.5, indicating a more robust capability in handling diverse data sources and preparing data for analysis.
- Reviewers mention that H2O's Model Training feature is highly rated at 9.2, showcasing its effectiveness in training models efficiently, whereas IBM Cloud Pak for Data, with a score of 8.8, is slightly less favored in this area, suggesting that H2O may provide a more streamlined experience for users focused on model development.
- G2 users highlight that H2O's Ease of Use is rated at 9.0, making it user-friendly for beginners, while IBM Cloud Pak for Data, with a score of 8.1, may present a steeper learning curve, particularly for those new to data science tools.
- Reviewers say that H2O's Quality of Support is rated at 8.8, indicating a strong support system, while IBM Cloud Pak for Data, with a score of 8.3, is still reliable but may not match the responsiveness and helpfulness reported by H2O users.
- Users on G2 report that H2O's Pre-Built Algorithms feature is highly rated at 9.4, which allows users to quickly implement machine learning solutions, while IBM Cloud Pak for Data, with a score of 9.1, also offers solid pre-built options but may not be as extensive as H2O's library.
- Reviewers mention that H2O's Data Visualization capabilities score 8.7, providing effective tools for visual data analysis, while IBM Cloud Pak for Data, with a score of 8.8, offers slightly better options, indicating that users may find more advanced visualization features in IBM's platform.
Pricing
Entry-Level Pricing
H2O
No pricing availableIBM Cloud Pak for Data
No pricing availableFree Trial
H2O
Free Trial is available
IBM Cloud Pak for Data
No trial information availableRatings
Meets Requirements
8.0
15
8.5
47
Ease of Use
9.0
14
8.1
47
Ease of Setup
7.8
6
7.2
26
Ease of Admin
8.3
6
7.6
27
Quality of Support
8.8
13
8.3
42
Has the product been a good partner in doing business?
8.3
5
8.1
25
Product Direction (% positive)
6.4
13
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
8.5
8
9.5
11
Model Development
8.3
8
8.3
8
8.3
8
8.5
8
9.4
8
9.1
9
9.2
8
8.8
8
Model Development
9.0
8
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
9.0
5
9.0
7
Machine/Deep Learning Services
Not enough data
9.2
8
9.0
5
9.3
7
Deployment
8.1
6
9.3
9
8.0
5
9.3
9
8.6
6
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
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
Core Functionality - Artificial Neural Network
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Data Handling - Artificial Neural Network
Not enough data
Not enough data
Not enough data
Not enough data
Performance - Artificial Neural Network
Not enough data
Not enough data
Not enough data
Not enough data
Usability - Artificial Neural Network
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Advanced Features - Artificial Neural Network
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
Agentic AI - Artificial Neural Network
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
Statistical Tool
8.1
6
8.3
5
Not enough data
8.8
8
8.3
5
8.6
7
Data Analysis
8.7
5
8.7
9
8.0
5
9.0
7
Decision Making
9.0
5
8.3
6
Not enough data
8.8
7
8.3
5
8.8
8
7.0
5
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
H2O and IBM Cloud Pak for Data are categorized as Data Science and Machine Learning Platforms, Predictive Analytics, and Generative AI Infrastructure
Unique Categories
H2O is categorized as Artificial Neural Network
IBM Cloud Pak for Data is categorized as Data Fabric, Virtual Private Cloud (VPC), Big Data Analytics, and Infrastructure as a Service (IaaS)
Reviews
Reviewers' Company Size
H2O
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
Financial Services
13.6%
Retail
9.1%
Research
9.1%
Marketing and Advertising
9.1%
Information Technology and Services
9.1%
Other
50.0%
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
H2O has no discussions with answers
IBM Cloud Pak for Data has no discussions with answers
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