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Compare IBM Cloud Pak for Data and TrendMiner 
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At a Glance
Market Segments
Enterprise (50.0% of reviews)
Enterprise (52.5% of reviews)
Entry-Level Pricing
No pricing available
Contact Us
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 DataTrendMiner
Star Rating
(181)4.6 out of 5
Market Segments
Enterprise (52.5% of reviews)
Pros & Cons
Entry-Level Pricing
Contact Us
Learn more about TrendMinerSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that IBM Cloud Pak for Data excels in Data Ingestion & Wrangling with a score of 9.5, making it a strong choice for organizations needing robust data preparation capabilities. In contrast, TrendMiner's performance in this area is not highlighted, suggesting it may not be as strong in data wrangling tasks.
- Reviewers mention that TrendMiner offers superior Quality of Support with a score of 9.2 compared to IBM Cloud Pak for Data's 8.3. This indicates that users may find more responsive and helpful support when using TrendMiner.
- G2 users highlight that TrendMiner has a better Ease of Use rating of 8.8, while IBM Cloud Pak for Data scores 8.1. This suggests that users may find TrendMiner more intuitive and user-friendly, which can be crucial for teams with varying technical expertise.
- Users on G2 report that IBM Cloud Pak for Data shines in Model Development with a high score of 9.1 for Pre-Built Algorithms, indicating a strong library of ready-to-use models. In contrast, TrendMiner's score of 7.8 in this area suggests it may not offer as extensive a selection.
- Reviewers mention that TrendMiner's Real-Time Analytics capabilities are rated at 8.8, which is competitive, but IBM Cloud Pak for Data's score of 8.5 indicates it also provides solid real-time data processing, making both products viable options for analytics needs.
- Users say that IBM Cloud Pak for Data's Customization options, particularly in Custom VMs, score 8.0, allowing for tailored solutions. However, TrendMiner's lack of specific customization features may limit flexibility for users with unique requirements.
Pricing
Entry-Level Pricing
IBM Cloud Pak for Data
No pricing availableTrendMiner
Custom
Contact Us
TrendMiner is priced to fit your company size. You can request more details here: https://www.trendminer.com/pricing/
- Custom pricing
Free Trial
IBM Cloud Pak for Data
No trial information availableTrendMiner
No trial information availableRatings
Meets Requirements
8.5
47
8.6
160
Ease of Use
8.1
47
8.8
164
Ease of Setup
7.2
26
8.4
61
Ease of Admin
7.6
27
8.5
37
Quality of Support
8.3
42
9.2
156
Has the product been a good partner in doing business?
8.1
25
9.3
44
Product Direction (% positive)
8.8
47
9.5
159
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
Data Management
Not enough data
8.3
71
Not enough data
7.7
69
Not enough data
7.6
65
Not enough data
8.5
69
Not enough data
7.6
63
Analytics
Not enough data
8.3
65
Not enough data
8.9
70
Not enough data
8.1
73
Agentic AI - Manufacturing Intelligence
Not enough data
5.2
10
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
Not enough data
Model Development
8.3
8
Not enough data
8.5
8
Not enough data
9.1
9
Not enough data
8.8
8
Not enough data
Model Development
8.5
12
Not enough data
Machine/Deep Learning Services
8.7
9
Not enough data
9.4
8
Not enough data
9.6
8
Not enough data
9.0
7
Not enough data
Machine/Deep Learning Services
9.2
8
Not enough data
9.3
7
Not enough data
Deployment
9.3
9
Not enough data
9.3
9
Not enough data
8.9
9
Not enough data
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 Sources
Not enough data
7.9
40
Not enough data
7.8
39
Not enough data
8.8
40
Analytics
Not enough data
8.1
39
Not enough data
8.1
39
Not enough data
8.8
40
Not enough data
8.5
40
Metrics
Not enough data
8.3
39
Not enough data
8.7
40
Not enough data
8.3
40
Not enough data
8.7
40
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
7.4
66
8.8
8
8.6
74
8.6
7
7.7
70
Data Analysis
8.7
9
9.0
80
9.0
7
8.5
76
Decision Making
8.3
6
8.0
76
8.8
7
8.9
81
8.8
8
8.2
75
8.3
8
8.3
72
Generative AI
Not enough data
6.6
45
Not enough data
6.6
45
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 TrendMiner are categorized as Predictive Analytics
Unique Categories
IBM Cloud Pak for Data is categorized as Data Fabric, Virtual Private Cloud (VPC), Big Data Analytics, Data Science and Machine Learning Platforms, Infrastructure as a Service (IaaS), and Generative AI Infrastructure
TrendMiner is categorized as Time Series Intelligence, Manufacturing Intelligence, and IoT Analytics Platforms
Reviews
Reviewers' Company Size
IBM Cloud Pak for Data
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
TrendMiner
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%
Chemicals
50.3%
Oil & Energy
7.8%
Computer Software
4.5%
Manufacturing
2.8%
Plastics
2.8%
Other
31.8%
Alternatives
Discussions
IBM Cloud Pak for Data has no discussions with answers
What is TrendMiner used for?
1 Comment
Official Response from TrendMiner
TrendMiner is used for advanced analytics in process manufacturing industries. Its primary functions and applications include:
Real-Time Monitoring: It...Read more
TrendMiner has no more discussions with answers
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