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- Databricks Data Intelligence Platform-vs-Red Hat OpenShift Data Science
Compare Databricks Data Intelligence Platform and Red Hat OpenShift Data Science 
At a Glance
Market Segments
Enterprise (46.8% of reviews)
Mid-Market (44.0% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Databricks Data Intelligence Platform
Star Rating
(609)4.6 out of 5
Market Segments
Enterprise (46.8% of reviews)
Entry-Level Pricing
No pricing available
Free Trial is available
Learn more about Databricks Data Intelligence PlatformRed Hat OpenShift Data Science
Star Rating
(25)4.4 out of 5
Market Segments
Mid-Market (44.0% of reviews)
Entry-Level Pricing
No pricing available
Learn more about Red Hat OpenShift Data ScienceSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that the Databricks Data Intelligence Platform excels in Data Lake Analytics with a score of 9.1, allowing for seamless integration and analysis of large datasets, while Red Hat OpenShift Data Science scores slightly lower at 8.9, indicating a less robust capability in this area.
- Reviewers mention that Red Hat OpenShift Data Science offers superior Language Support with a score of 9.1 compared to Databricks' 8.5, making it a better choice for teams working with diverse programming languages.
- G2 users highlight that Databricks shines in Model Registry functionality, scoring 8.9, which facilitates better management of machine learning models, whereas Red Hat has a slightly lower score of 8.6, suggesting less comprehensive model management features.
- Users on G2 report that Red Hat OpenShift Data Science provides a more user-friendly experience with its Drag and Drop feature, scoring 8.8, compared to Databricks' score of 7.5, indicating that Red Hat may be easier for new users to navigate.
- Reviewers mention that Databricks has a strong edge in Data Integration with a score of 9.0, which is crucial for organizations needing to combine data from various sources, while Red Hat's score of 8.9 shows it is competitive but not quite as strong.
- Users say that Red Hat OpenShift Data Science excels in Automated Workflows with a score of 8.9, which enhances productivity by streamlining processes, while Databricks scores 8.8, indicating a slightly less efficient workflow automation capability.
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Pricing
Entry-Level Pricing
Databricks Data Intelligence Platform
No pricing availableRed Hat OpenShift Data Science
No pricing availableFree Trial
Databricks Data Intelligence Platform
Free Trial is available
Red Hat OpenShift Data Science
No trial information availableRatings
Meets Requirements
8.9
495
8.8
23
Ease of Use
8.8
504
8.5
23
Ease of Setup
8.7
377
Not enough data
Ease of Admin
8.3
162
Not enough data
Quality of Support
8.7
470
8.6
21
Has the product been a good partner in doing business?
8.8
165
Not enough data
Product Direction (% positive)
9.6
484
10.0
23
Features by Category
Administration
8.7
84
Not enough data
8.6
81
Not enough data
9.0
82
Not enough data
8.6
83
Not enough data
Management
8.4
76
Not enough data
8.6
75
Not enough data
8.6
75
Not enough data
8.4
75
Not enough data
8.7
75
Not enough data
Compliance
8.8
82
Not enough data
8.6
81
Not enough data
8.9
80
Not enough data
8.7
80
Not enough data
Security
8.9
73
Not enough data
8.8
75
Not enough data
8.8
75
Not enough data
Data Quality
8.9
82
Not enough data
8.7
81
Not enough data
9.0
79
Not enough data
Maintainence
8.8
74
Not enough data
8.8
73
Not enough data
Generative AI
8.4
72
Not enough data
8.6
71
Not enough data
Agentic AI - Data Governance
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
8.6
161
Not enough data
8.5
155
Not enough data
Functionality
9.1
162
Not enough data
9.2
163
Not enough data
9.1
164
Not enough data
9.0
156
Not enough data
9.1
158
Not enough data
Deployment
8.9
61
Not enough data
8.9
62
Not enough data
8.9
62
Not enough data
8.9
62
Not enough data
8.9
62
Not enough data
Deployment
8.9
60
Not enough data
8.8
61
Not enough data
8.6
64
Not enough data
8.9
63
Not enough data
9.0
63
Not enough data
Management
8.9
59
Not enough data
8.8
61
Not enough data
9.2
57
Not enough data
9.0
65
Not enough data
Operations
8.7
60
Not enough data
8.8
59
Not enough data
9.0
60
Not enough data
Management
8.8
59
Not enough data
8.7
58
Not enough data
9.1
57
Not enough data
Generative AI
8.3
26
Not enough data
8.3
26
Not enough data
System
8.9
169
8.9
22
8.7
164
9.1
23
8.1
165
8.7
23
Model Development
8.7
172
8.8
23
7.9
178
8.8
23
8.3
175
8.7
23
8.6
177
8.6
23
Model Development
8.4
163
8.5
22
8.6
167
8.6
22
8.5
165
8.8
23
Machine/Deep Learning Services
8.1
164
8.5
22
8.5
169
8.3
20
8.2
161
8.6
20
8.2
163
8.3
20
Machine/Deep Learning Services
8.2
152
8.8
22
8.4
150
8.6
20
8.4
150
8.6
20
8.5
152
8.7
21
Deployment
8.5
167
8.6
22
8.7
170
8.8
22
9.0
174
8.5
22
Deployment
8.5
157
8.8
23
8.7
163
8.7
23
8.8
161
8.6
23
Generative AI
8.3
81
8.3
5
8.5
81
8.7
5
7.6
80
8.7
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
9.0
171
|
Verified
Not enough data
8.9
170
|
Verified
Not enough data
8.8
165
|
Verified
Not enough data
8.7
168
|
Verified
Not enough data
8.6
158
|
Verified
Not enough data
9.0
160
|
Verified
Not enough data
Integration
8.8
156
|
Verified
Not enough data
8.8
156
|
Verified
Not enough data
9.0
164
|
Verified
Not enough data
Deployment
7.8
145
|
Verified
Not enough data
9.1
166
|
Verified
Not enough data
Performance
9.1
166
|
Verified
Not enough data
Security
8.8
157
|
Verified
Not enough data
8.9
158
|
Verified
Not enough data
Generative AI
8.5
68
Not enough data
8.4
67
Not enough data
Data Management
9.0
60
Not enough data
8.6
59
Not enough data
8.7
60
Not enough data
9.1
57
Not enough data
Agentic AI - DataOps 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
Analytics
8.9
58
Not enough data
8.5
57
Not enough data
Monitoring and Management
8.6
58
Not enough data
8.4
58
Not enough data
Cloud Deployment
9.1
54
Not enough data
9.0
55
Not enough data
Generative AI
8.9
29
Not enough data
9.0
29
Not enough data
Database
8.7
202
Not enough data
8.9
208
Not enough data
9.3
209
Not enough data
Integrations
8.2
191
Not enough data
9.2
211
Not enough data
Platform
9.0
204
Not enough data
8.8
207
Not enough data
9.2
211
Not enough data
Processing
9.0
204
Not enough data
9.0
203
Not enough data
Data Transformation
8.8
210
Not enough data
9.0
217
Not enough data
Connectivity
8.6
193
Not enough data
9.2
216
Not enough data
9.0
208
Not enough data
9.2
216
Not enough data
Operations
8.4
214
Not enough data
8.8
209
Not enough data
8.6
198
Not enough data
8.6
196
Not enough data
9.3
211
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
Databricks Data Intelligence Platform and Red Hat OpenShift Data Science are categorized as Data Science and Machine Learning Platforms
Unique Categories
Databricks Data Intelligence Platform is categorized as DataOps Platforms, MLOps Platforms, ETL Tools, Big Data Processing and Distribution, Big Data Analytics, Data Warehouse, and Data Governance
Red Hat OpenShift Data Science has no unique categories
Reviews
Reviewers' Company Size
Databricks Data Intelligence Platform
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
14.6%
Financial Services
11.7%
Computer Software
7.7%
Consulting
4.0%
Hospital & Health Care
3.9%
Other
58.1%
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%
Most Helpful Reviews
Databricks Data Intelligence Platform
Most Helpful Favorable Review
Alihan Z.
Verified User in Telecommunications
A great experience that combines ML-Runtimes - MLFlow and Spark. The ability to use Python, and SQL seamlessly in one platform. Since databricks notebooks can be saved as python scripts in the background it is amazing to have both notebook and script...
Most Helpful Critical Review
Aleksandr P.
Verified User in Financial Services
The biggest kink in Lakehouse platform is its speed. It does not deliver on the performance promised. In addition, the Databricks UI is not easy to use. It feels like it's a smartphone app. On the side of technology, it is slow and expensive, with...
Red Hat OpenShift Data Science
Most Helpful Favorable Review
Margaret Z.
Verified User in Market Research
I love this instrument because this platform gives automatic learning tools and models for prototypes quickly of study models and apply them to the data of your organization, it is a cloud application containers platform that allows you to produce, carry...
Most Helpful Critical Review
Alihan Z.
Verified User in Telecommunications
A great experience that combines ML-Runtimes - MLFlow and Spark. The ability to use Python, and SQL seamlessly in one platform. Since databricks notebooks can be saved as python scripts in the background it is amazing to have both notebook and script...
Margaret Z.
Verified User in Market Research
I love this instrument because this platform gives automatic learning tools and models for prototypes quickly of study models and apply them to the data of your organization, it is a cloud application containers platform that allows you to produce, carry...
Aleksandr P.
Verified User in Financial Services
The biggest kink in Lakehouse platform is its speed. It does not deliver on the performance promised. In addition, the Databricks UI is not easy to use. It feels like it's a smartphone app. On the side of technology, it is slow and expensive, with...
Alternatives
Discussions
What is Lakehouse in Databricks?
4 comments
BR
Lakehouse is a new and open data management architecture solution that combines the best features of the data lake and warehouse.Read more
What are the features of Databricks?
3 comments
SA
It supports large amount of data with capability to write code in SQL, Spark, Python and R.
In the backend, it stored the data in the parquet file which...Read more
What is Databricks unified analytics platform?
3 comments
CA
Databricks' Unified Data Analytics Platform helps organizations accelerate innovation by unifying data science with engineering and business. With Databricks...Read more
Red Hat OpenShift Data Science has no discussions with answers
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