Compare Databricks and Red Hat OpenShift Data Science 
At a Glance
Market Segments
Enterprise (44.3% of reviews)
Mid-Market (44.0% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Databricks
Star Rating
(755)4.6 out of 5
Market Segments
Enterprise (44.3% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about DatabricksRed Hat OpenShift Data Science
Star Rating
(25)4.4 out of 5
Market Segments
Mid-Market (44.0% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about Red Hat OpenShift Data ScienceSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that Databricks excels in providing a comprehensive data workflow solution, with features like Genie, Lakehouse Connect, and streaming tables that streamline data processing and analysis. Users appreciate the all-in-one platform that reduces the need to switch between multiple tools.
- Users say that Red Hat OpenShift Data Science offers excellent performance and ease of use, particularly highlighting its containerization capabilities. This feature allows for unrivaled scalability and flexibility, making it a strong choice for managing complex data science workflows, especially in finance.
- Reviewers mention that Databricks has a significantly higher overall satisfaction score compared to Red Hat OpenShift Data Science, indicating a more favorable user experience. The platform's Unity Catalog has been noted as a game-changer for centralized governance and access control, enhancing data management for enterprises.
- According to verified reviews, Red Hat OpenShift Data Science is praised for its robust support and documentation, which users find extremely helpful. This level of support contributes to a positive experience, especially for teams new to data science workflows.
- G2 reviewers highlight that Databricks has a more extensive user base and recent activity, with a significantly higher number of reviews. This suggests a more active community and ongoing improvements, which can be crucial for users seeking reliable and up-to-date solutions.
- Users report that while both platforms have strong features, Databricks leads in ease of use and setup, with many users noting the intuitive onboarding process. In contrast, some users of Red Hat OpenShift Data Science have expressed challenges in adapting to its unique containerization approach.
Pricing
Entry-Level Pricing
Databricks
No pricing availableRed Hat OpenShift Data Science
No pricing availableFree Trial
Databricks
Free Trial is available
Red Hat OpenShift Data Science
No trial information availableRatings
Meets Requirements
8.9
592
8.8
23
Ease of Use
8.9
607
8.5
23
Ease of Setup
8.7
479
Not enough data
Ease of Admin
8.4
184
Not enough data
Quality of Support
8.7
568
8.6
21
Has the product been a good partner in doing business?
8.9
188
Not enough data
Product Direction (% positive)
9.6
579
10.0
23
Features by Category
Reports
8.5
14
Not enough data
7.9
12
Not enough data
8.5
12
Not enough data
8.2
10
Not enough data
9.1
16
Not enough data
Data Preparation
9.0
7
Not enough data
9.0
8
Not enough data
Data Modeling and Blending
9.1
9
Not enough data
9.0
8
Not enough data
8.9
9
Not enough data
Generative AI
9.2
10
Not enough data
9.3
7
Not enough data
Agentic AI - Analytics Platforms
9.4
8
Not enough data
8.9
6
Not enough data
8.6
7
Not enough data
8.6
7
Not enough data
8.5
8
Not enough data
9.3
7
Not enough data
9.4
6
Not enough data
Self Service
7.9
11
Not enough data
7.9
11
Not enough data
8.6
12
Not enough data
8.2
13
Not enough data
8.3
12
Not enough data
8.1
9
Not enough data
Deployment & Integration - Analytics Platforms
8.3
8
Not enough data
9.3
9
Not enough data
8.8
7
Not enough data
9.3
7
Not enough data
Advanced Analytics
8.5
12
Not enough data
8.3
12
Not enough data
9.2
14
Not enough data
Performance & Scalability - Analytics Platforms
9.0
8
Not enough data
9.7
5
Not enough data
Advanced Analytics & Modeling - Analytics Platforms
9.1
9
Not enough data
8.7
9
Not enough data
8.8
7
Not enough data
Agentic AI Capabilities - Analytics Platforms
8.8
8
Not enough data
9.0
8
Not enough data
9.0
7
Not enough data
8.8
8
Not enough data
Personalized Intelligence - Analytics Platforms
9.3
7
Not enough data
8.1
9
Not enough data
8.5
8
Not enough data
Building Reports
9.0
158
Not enough data
8.6
149
Not enough data
7.6
124
Not enough data
8.4
149
Not enough data
Administration
8.8
100
Not enough data
8.6
94
Not enough data
9.0
95
Not enough data
8.7
99
Not enough data
Management
8.5
88
Not enough data
8.6
87
Not enough data
8.7
89
Not enough data
8.5
88
Not enough data
8.8
87
Not enough data
Compliance
8.9
100
Not enough data
8.7
93
Not enough data
8.9
95
Not enough data
8.7
96
Not enough data
Security
9.0
89
Not enough data
8.9
87
Not enough data
8.8
87
Not enough data
Data Quality
9.0
95
Not enough data
8.7
94
Not enough data
9.0
94
Not enough data
Maintainence
8.7
86
Not enough data
8.8
85
Not enough data
Generative AI
8.4
83
Not enough data
8.5
82
Not enough data
Agentic AI - Data Governance
8.6
11
Not enough data
8.9
12
Not enough data
9.1
15
Not enough data
8.6
13
Not enough data
9.1
13
Not enough data
9.0
14
Not enough data
Management
8.6
173
Not enough data
8.5
165
Not enough data
Functionality
9.1
177
Not enough data
9.2
179
Not enough data
9.1
174
Not enough data
9.0
168
Not enough data
9.1
170
Not enough data
Deployment
8.9
65
Not enough data
8.9
64
Not enough data
8.9
66
Not enough data
8.9
66
Not enough data
9.0
68
Not enough data
Deployment
8.9
62
Not enough data
8.8
62
Not enough data
8.6
66
Not enough data
8.9
65
Not enough data
9.0
66
Not enough data
Management
9.0
64
Not enough data
8.9
66
Not enough data
9.2
61
Not enough data
9.0
69
Not enough data
Operations
8.7
62
Not enough data
8.8
62
Not enough data
9.0
63
Not enough data
Management
8.8
61
Not enough data
8.7
61
Not enough data
9.1
59
Not enough data
Generative AI
8.3
28
Not enough data
8.3
28
Not enough data
System
8.9
181
8.9
22
Model Development
8.7
184
8.8
23
8.0
188
8.8
23
8.3
187
8.7
23
8.7
192
8.6
23
Model Development
8.5
173
8.8
23
Machine/Deep Learning Services
8.2
175
8.5
22
8.5
181
8.3
20
8.3
173
8.6
20
8.2
173
8.3
20
Machine/Deep Learning Services
8.4
159
8.6
20
8.4
161
8.7
21
Deployment
8.5
180
8.6
22
8.7
181
8.8
22
9.0
189
8.5
22
Generative AI
8.2
87
8.3
5
8.4
88
8.7
5
7.6
87
8.7
5
Agentic AI - Data Science and Machine Learning Platforms
9.3
9
Not enough data
8.5
8
Not enough data
8.3
9
Not enough data
8.8
8
Not enough data
9.2
11
Not enough data
8.8
7
Not enough data
9.4
8
Not enough data
Data Management
9.1
186
|
Verified
Not enough data
8.9
181
|
Verified
Not enough data
8.9
182
|
Verified
Not enough data
8.8
181
|
Verified
Not enough data
8.7
168
|
Verified
Not enough data
9.1
173
|
Verified
Not enough data
Integration
8.8
169
|
Verified
Not enough data
8.8
168
|
Verified
Not enough data
9.1
177
|
Verified
Not enough data
Deployment
7.9
157
|
Verified
Not enough data
9.2
179
|
Verified
Not enough data
Performance
9.2
180
|
Verified
Not enough data
Security
8.9
171
|
Verified
Not enough data
8.9
169
|
Verified
Not enough data
Generative AI
8.5
77
Not enough data
8.4
76
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
Maintenance
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
Data Management
9.0
69
Not enough data
8.8
71
Not enough data
8.8
69
Not enough data
9.1
70
Not enough data
Agentic AI - DataOps Platforms
9.2
10
Not enough data
9.0
8
Not enough data
9.0
10
Not enough data
9.1
9
Not enough data
9.4
9
Not enough data
Analytics
8.8
68
Not enough data
8.6
68
Not enough data
Monitoring and Management
8.6
68
Not enough data
8.6
69
Not enough data
Cloud Deployment
9.0
64
Not enough data
9.0
65
Not enough data
Generative AI
9.0
37
Not enough data
8.9
37
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
Customization - AI Agent Builders
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Functionality - AI Agent Builders
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 and Analytics - AI Agent Builders
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Integration - AI Agent Builders
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Traffic Management & Performance - AI Gateways
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Governance & Observability - AI Gateways
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Database
8.7
239
Not enough data
8.9
247
Not enough data
9.3
265
Not enough data
Integrations
8.3
220
Not enough data
9.1
268
Not enough data
Platform
9.0
261
Not enough data
8.9
255
Not enough data
9.1
268
Not enough data
Processing
9.0
248
Not enough data
9.0
255
Not enough data
Data Transformation
8.9
229
Not enough data
9.1
237
Not enough data
Connectivity
8.7
208
Not enough data
9.2
232
Not enough data
9.0
222
Not enough data
9.2
232
Not enough data
Operations
8.4
230
Not enough data
8.8
229
Not enough data
8.6
214
Not enough data
8.6
210
Not enough data
9.3
233
Not enough data
Building Reports
9.0
158
Not enough data
8.6
149
Not enough data
7.6
124
Not enough data
8.4
149
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
Databricks and Red Hat OpenShift Data Science are categorized as Data Science and Machine Learning Platforms
Unique Categories
Red Hat OpenShift Data Science has no unique categories
Reviews
Reviewers' Company Size
Databricks
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Red Hat OpenShift Data Science
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
Information Technology and Services
15.8%
Financial Services
10.3%
Computer Software
8.6%
Consulting
3.9%
Hospital & Health Care
3.7%
Other
57.7%
Market Research
32.0%
Marketing and Advertising
20.0%
Information Technology and Services
8.0%
Computer Software
8.0%
Transportation/Trucking/Railroad
4.0%
Other
28.0%
Alternatives
Discussions
What is Lakehouse in Databricks?
4 Comments
BK
Lakehouse architecture is the merging of the data warehouse and data lake concepts into a single platform, with built-in support for lineage maintenance and ML.Read more
What are the features of Databricks?
4 Comments
SM
Delta Lake
Lakehosue platform
Schema evolution
Data quarantine & Data Quality
Data Integration & TransformationsRead more
What does Databricks software do?
3 Comments
SM
It will work like Hadoop, databricks provide the services like big data.
Databricks also work like in advanced level it's have capability to process large...Read more
Red Hat OpenShift Data Science has no discussions with answers
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