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Compare Dremio and IBM Cloud Pak for Data 
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At a Glance
Market Segments
Enterprise (47.6% of reviews)
Enterprise (50.0% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Dremio
Star Rating
(69)4.6 out of 5
Market Segments
Enterprise (47.6% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about DremioIBM 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 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, Dremio, while also effective, does not match this level of performance in this specific area.
- Reviewers mention that Dremio shines in Ease of Use with a score of 9.1, indicating a more user-friendly interface compared to IBM Cloud Pak for Data, which scored 8.1. This makes Dremio a preferred option for teams looking for a straightforward user experience.
- G2 users highlight that Dremio's Data Querying capabilities are superior, scoring 9.2, which allows for faster and more efficient data retrieval compared to IBM Cloud Pak for Data's score of 9.1. This can significantly impact performance in data-heavy environments.
- Reviewers say that IBM Cloud Pak for Data offers better Customization options, particularly with its support for Custom VMs, which allows for tailored infrastructure setups. Dremio, while flexible, does not provide the same level of customization in this regard.
- Users on G2 report that Dremio's Data Lake Integration is highly rated at 9.1, making it an excellent choice for organizations heavily invested in data lakes. IBM Cloud Pak for Data, while capable, does not match this integration strength.
- Reviewers mention that IBM Cloud Pak for Data has a strong focus on Data Security with a compliance score of 9.0, which is crucial for enterprises concerned about data governance. Dremio, while secure, does not emphasize this aspect to the same extent.
Pricing
Entry-Level Pricing
Dremio
No pricing availableIBM Cloud Pak for Data
No pricing availableFree Trial
Dremio
Free Trial is available
IBM Cloud Pak for Data
No trial information availableRatings
Meets Requirements
8.7
52
8.5
47
Ease of Use
9.2
53
8.1
47
Ease of Setup
8.4
47
7.2
26
Ease of Admin
7.8
29
7.6
27
Quality of Support
8.5
50
8.3
42
Has the product been a good partner in doing business?
9.1
28
8.1
25
Product Direction (% positive)
9.7
46
8.8
47
Features by Category
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
Not enough data
Not enough data
Self Service
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
Advanced Analytics
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
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
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
Data Management
8.6
23
Not enough data
8.5
20
Not enough data
8.3
12
Not enough data
7.7
20
Not enough data
Feature Not Available
Not enough data
8.9
23
Not enough data
Integration
Feature Not Available
Not enough data
8.8
21
Not enough data
9.0
22
Not enough data
Deployment
8.7
15
Not enough data
8.5
19
Not enough data
Performance
8.3
21
Not enough data
Security
8.2
20
Not enough data
Feature Not Available
Not enough data
Generative AI
6.9
12
Not enough data
Not enough data
Not enough data
Data Management
8.6
11
Not enough data
8.8
11
Not enough data
Feature Not Available
Not enough data
Data as a Service
7.6
11
Not enough data
8.2
11
Not enough data
Architecture
8.2
11
Not enough data
8.6
11
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
Deployment & Integration - Semantic Layer Tools
Not enough data
Not enough data
Not enough data
Not enough data
Data Connectivity & Federation - Semantic Layer Tools
Not enough data
Not enough data
Not enough data
Not enough data
Data Modeling & Metrics - Semantic Layer Tools
Not enough data
Not enough data
Not enough data
Not enough data
Performance Optimization - Semantic Layer Tools
Not enough data
Not enough data
Not enough data
Not enough data
Governance - Semantic Layer Tools
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Advanced Intelligence - Semantic Layer Tools
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI Enablement - Semantic Layer Tools
Not enough data
Not enough data
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
Not enough data
Not enough data
Not enough data
Database
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Integrations
9.0
18
Not enough data
7.9
13
Not enough data
Platform
9.1
20
Not enough data
8.7
13
Not enough data
7.9
13
Not enough data
Processing
9.1
18
Not enough data
8.6
13
Not enough data
Data Transformation
Feature Not Available
8.5
27
|
Verified
9.2
24
9.1
15
|
Verified
Connectivity
8.6
22
8.0
23
|
Verified
Feature Not Available
8.6
22
|
Verified
8.9
23
8.1
25
|
Verified
8.9
25
8.7
24
|
Verified
Operations
7.2
25
8.7
26
|
Verified
7.1
25
8.9
25
|
Verified
7.8
27
8.4
23
|
Verified
7.7
21
8.8
24
|
Verified
7.0
21
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
Dremio and IBM Cloud Pak for Data are categorized as Big Data Analytics
Unique Categories
Dremio is categorized as Big Data Processing and Distribution, Data Warehouse, Data as a Service (DaaS), and Semantic Layer Tools
IBM Cloud Pak for Data is categorized as Data Fabric, Virtual Private Cloud (VPC), Data Science and Machine Learning Platforms, Predictive Analytics, Infrastructure as a Service (IaaS), and Generative AI Infrastructure
Reviews
Reviewers' Company Size
Dremio
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
23.8%
Information Technology and Services
11.1%
Computer Software
7.9%
Marketing and Advertising
4.8%
Automotive
4.8%
Other
47.6%
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
What is a Dremio reflection?
1 Comment
Official Response from Dremio
A reflection is an optimized materialization of source data or a query, similar to a materialized view, that is derived from an existing table or view. A...Read more
Dremio has no more discussions with answers
IBM Cloud Pak for Data has no discussions with answers
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