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Compare IBM Cloud Pak for Data and Posit 
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At a Glance
Market Segments
Enterprise (50.0% of reviews)
Enterprise (48.6% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
IBM 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 DataPosit
Star Rating
(562)4.5 out of 5
Market Segments
Enterprise (48.6% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about PositSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Posit excels in data ingestion and wrangling with a score of 9.1, 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 formats.
- Reviewers mention that Posit offers a user-friendly drag-and-drop interface with a score of 7.4, but IBM Cloud Pak for Data significantly outperforms it with a score of 9.0, making it easier for users to create visualizations and workflows without extensive coding knowledge.
- G2 users highlight that Posit has strong data governance features, scoring 9.0, while IBM Cloud Pak for Data also performs well in this area, but with a slightly lower score of 8.8, suggesting that Posit may provide a more comprehensive approach to data compliance and management.
- Users on G2 report that Posit’s model training capabilities are impressive, scoring 9.1, but IBM Cloud Pak for Data is competitive with a score of 8.8, indicating that both platforms are effective for machine learning tasks, though Posit may have a slight edge in this specific area.
- Reviewers mention that while both products support cloud deployment, IBM Cloud Pak for Data stands out with a managed service score of 9.3 compared to Posit’s 8.2, suggesting that IBM offers a more seamless and reliable cloud experience for users.
- Users say that Posit’s data visualization capabilities are rated at 8.9, which is commendable, but IBM Cloud Pak for Data slightly surpasses it with a score of 8.8, indicating that both platforms provide valuable tools for data representation, though Posit may have a marginal advantage in this area.
Pricing
Entry-Level Pricing
IBM Cloud Pak for Data
No pricing availablePosit
No pricing availableFree Trial
IBM Cloud Pak for Data
No trial information availablePosit
Free Trial is available
Ratings
Meets Requirements
8.5
47
9.1
496
Ease of Use
8.1
47
8.3
496
Ease of Setup
7.2
26
8.8
106
Ease of Admin
7.6
27
8.3
90
Quality of Support
8.3
42
8.1
403
Has the product been a good partner in doing business?
8.1
25
8.5
81
Product Direction (% positive)
8.8
47
8.5
488
Features by Category
Customization
8.0
5
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Infrastructure
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
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
Administration
Not enough data
8.7
76
Not enough data
9.2
82
Not enough data
8.2
76
Capabilities
Not enough data
9.0
89
Not enough data
8.9
67
Not enough data
8.9
55
Not enough data
8.8
59
Methodology
Not enough data
9.1
77
Not enough data
9.5
85
Not enough data
9.3
82
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Infrastructure Provision
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
Not enough data
Management
8.6
7
Not enough data
8.3
7
Not enough data
8.1
8
Not enough data
Functionality
8.3
8
Not enough data
System
9.5
11
9.1
25
Model Development
8.3
8
8.8
19
8.5
8
7.8
21
9.1
9
8.3
21
8.8
8
9.0
21
Model Development
8.5
12
9.0
20
Machine/Deep Learning Services
8.7
9
8.6
15
9.4
8
8.5
14
9.6
8
8.7
13
9.0
7
7.6
17
Machine/Deep Learning Services
9.2
8
8.6
17
9.3
7
9.1
18
Deployment
9.3
9
8.4
19
9.3
9
8.9
18
8.9
9
8.7
19
Generative AI
8.3
5
Not enough data
8.3
5
Not enough data
8.3
5
Not enough data
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
8.3
5
Not enough data
Analytics
Not enough data
Not enough data
Security
9.0
5
Not enough data
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
Statistical Tool
8.3
5
Not enough data
8.8
8
Not enough data
8.6
7
Not enough data
Data Analysis
8.7
9
Not enough data
9.0
7
Not enough data
Decision Making
8.3
6
Not enough data
8.8
7
Not enough data
8.8
8
Not enough data
8.3
8
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Database
Not enough data
9.0
8
Not enough data
9.0
7
Not enough data
8.6
7
Integrations
Not enough data
8.3
5
Not enough data
8.3
6
Platform
Not enough data
7.9
8
Not enough data
8.7
10
Not enough data
8.3
6
Processing
Not enough data
8.3
5
Not enough data
8.1
8
Data Transformation
8.5
27
|
Verified
Not enough data
9.1
15
|
Verified
Not enough data
Connectivity
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
Not enough data
Operations
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
Not enough data
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
IBM Cloud Pak for Data and Posit are categorized as Data Science and Machine Learning Platforms
Unique Categories
IBM Cloud Pak for Data is categorized as Data Fabric, Virtual Private Cloud (VPC), Big Data Analytics, Predictive Analytics, Infrastructure as a Service (IaaS), and Generative AI Infrastructure
Posit is categorized as Statistical Analysis and Big Data Processing and Distribution
Reviews
Reviewers' Company Size
IBM Cloud Pak for Data
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Posit
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
Computer Software
12.9%
Information Technology and Services
8.6%
Banking
8.6%
Financial Services
5.7%
Education Management
5.7%
Other
58.6%
Higher Education
19.1%
Information Technology and Services
12.6%
Research
11.2%
Computer Software
8.7%
Education Management
5.6%
Other
42.8%
Alternatives
Discussions
IBM Cloud Pak for Data has no discussions with answers
Can we save our process if we don't save a project?
2 Comments
SL
There are many ways to save results as an R script runs, take a look at the R saveRDS function as one example.
For questions like this about R a great...Read more
What is the best way to run R code within a VBA routine?
1 Comment
PB
I ran into same kind of problems. Then I discovered PowerBI.
With PowerBI, and the help of PowerQuery, I'm getting rid of all VbA engines to process...Read more
Which software is used for R programming?
1 Comment
SH
RStudio is the most popular IDE for running R programs and has a free license. The official R software environment is an open-source free software...Read more
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