Compare Cinchy and IBM Cloud Pak for Data 
At a Glance
Market Segments
Mid-Market (50.0% of reviews)
Enterprise (50.0% of reviews)
Entry-Level Pricing
$$
No pricing available
Cinchy
Star Rating
(20)4.8 out of 5
Market Segments
Mid-Market (50.0% of reviews)
Entry-Level Pricing
$$
Browse all 2 pricing plansIBM Cloud Pak for Data
Star Rating
(90)4.3 out of 5
Market Segments
Enterprise (50.0% of reviews)
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 excels in Data Integration, with a score of 9.9, making it a strong choice for organizations needing robust data management capabilities. In contrast, Cinchy, while also effective, has a slightly lower score in this area, indicating it may not be as comprehensive for data integration tasks.
- Reviewers mention that Cinchy shines in Quality of Support, achieving a remarkable score of 9.7. Users appreciate the responsiveness and helpfulness of the support team, while IBM Cloud Pak for Data, with a score of 8.3, has room for improvement in this critical area.
- G2 users highlight the Ease of Use of Cinchy, which scored 9.4, making it particularly appealing for teams looking for a user-friendly interface. In comparison, IBM Cloud Pak for Data's score of 8.1 suggests that it may require a steeper learning curve for new users.
- Users on G2 report that IBM Cloud Pak for Data offers superior Data Ingestion & Wrangling capabilities, scoring 9.5, which is essential for organizations dealing with large volumes of data. Cinchy, while effective, does not match this level of performance, indicating a potential gap for users focused on data preparation.
- Reviewers mention that Cinchy's Real-Time Integration capabilities are impressive, scoring 9.0, which is crucial for businesses needing immediate data updates. IBM Cloud Pak for Data, while strong in many areas, does not emphasize real-time integration to the same extent, which could be a deciding factor for some users.
- Users say that IBM Cloud Pak for Data's Scalability is a significant advantage, particularly for enterprise-level applications, with a score of 8.9. In contrast, Cinchy's scalability score of 9.1 indicates it may be better suited for mid-market companies, suggesting that larger enterprises might find IBM's offering more robust for their needs.
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Pricing
Entry-Level Pricing
IBM Cloud Pak for Data
No pricing availableFree Trial
Cinchy
No trial information availableIBM Cloud Pak for Data
No trial information availableRatings
Meets Requirements
8.9
16
8.5
49
Ease of Use
9.4
16
8.1
49
Ease of Setup
7.2
10
7.2
27
Ease of Admin
8.3
9
7.6
27
Quality of Support
9.7
16
8.3
44
Has the product been a good partner in doing business?
10.0
11
8.1
25
Product Direction (% positive)
10.0
16
8.8
49
Features by Category
Data Integration
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 Analysis & Optimization
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
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
Management
Not enough data
Not enough data
Not enough data
Not enough data
Functionality
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 Sourcing
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Intelligence
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
Not enough data
8.8
11
Not enough data
9.0
10
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
7.8
12
Not enough data
8.5
10
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
8.5
9
Not enough data
9.2
8
Not enough data
8.7
9
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
Deployment
Not enough data
8.5
10
Not enough data
8.8
11
Not enough data
9.1
11
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Data Management
9.9
13
Not enough data
9.3
12
Not enough data
9.8
8
Not enough data
9.6
8
8.3
5
Analytics
10.0
8
Not enough data
Security
10.0
8
9.0
5
9.8
10
Not enough data
10.0
10
Not enough data
Generative AI
Feature Not Available
Feature Not Available
Feature Not Available
Feature Not Available
Development
9.0
5
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
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
Security
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Integration Options
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Deployment
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
Not enough data
Analytics
Not enough data
Not enough data
Not enough data
Not enough data
Monitoring and Management
Not enough data
Not enough data
Not enough data
Not enough data
Cloud Deployment
Not enough data
Not enough data
Not enough data
Not enough data
Generative AI
Feature Not Available
Not enough data
Feature Not Available
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
Feature Not Available
Not enough data
Feature Not Available
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
Cinchy and IBM Cloud Pak for Data are categorized as Data Fabric
Unique Categories
Cinchy is categorized as Customer Data Platform (CDP), iPaaS, ETL Tools, Data Management Platform (DMP), On-Premise Data Integration, Data Management Suites, and DataOps Platforms
IBM Cloud Pak for Data is categorized as Virtual Private Cloud (VPC), Big Data Analytics, Data Science and Machine Learning Platforms, Predictive Analytics, Infrastructure as a Service (IaaS), and Generative AI Infrastructure
Reviews
Reviewers' Company Size
Cinchy
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
45.0%
Banking
20.0%
Insurance
15.0%
Venture Capital & Private Equity
5.0%
Retail
5.0%
Other
10.0%
Computer Software
12.5%
Information Technology and Services
9.7%
Banking
8.3%
Financial Services
5.6%
Education Management
5.6%
Other
58.3%
Most Helpful Reviews
Cinchy
Most Helpful Favorable Review
Verified User in Insurance
The Cinchy Platform helped us transition to becoming a more data enabled organization. In partifular it helped us: -Consolidate siloed data from different applications into one central location -Enabled us to build sophisticated reports and dashboards to...
Most Helpful Critical Review
IBM Cloud Pak for Data
Most Helpful Favorable Review
Nagaraj Kumar N.
Verified User in Consumer Electronics
We didn't have any other product in market that matches ICP4D All products are public cloud focused. No product vendors are focusing the private cloud . ICP address it.
Most Helpful Critical Review
Verified User in Health, Wellness and Fitness
Challenges accross multiple cloud environments
Verified User in Insurance
The Cinchy Platform helped us transition to becoming a more data enabled organization. In partifular it helped us: -Consolidate siloed data from different applications into one central location -Enabled us to build sophisticated reports and dashboards to...
Nagaraj Kumar N.
Verified User in Consumer Electronics
We didn't have any other product in market that matches ICP4D All products are public cloud focused. No product vendors are focusing the private cloud . ICP address it.
Verified User in Health, Wellness and Fitness
Challenges accross multiple cloud environments
Alternatives
Discussions
Cinchy has no discussions with answers
IBM Cloud Pak for Data has no discussions with answers
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