Introducing G2.ai, the future of software buying.Try now
Compare Palantir Gotham and Red Hat OpenShift Data Science 
Featured Products
Sponsored
You’re seeing this ad based on the product’s relevance to this page. Sponsored content does not receive preferential treatment in any of G2’s ratings.
Alteryx
Visit Website
Sponsored
You’re seeing this ad based on the product’s relevance to this page. Sponsored content does not receive preferential treatment in any of G2’s ratings.
MindCloud
Visit Website
Sponsored
You’re seeing this ad based on the product’s relevance to this page. Sponsored content does not receive preferential treatment in any of G2’s ratings.
Omatic Software
Visit Website
At a Glance
Market Segments
Mid-Market (37.5% of reviews)
Mid-Market (44.0% of reviews)
Pros & Cons
Not enough data
Not enough data
Entry-Level Pricing
No pricing available
No pricing available
Palantir Gotham
Star Rating
(10)4.3 out of 5
Market Segments
Mid-Market (37.5% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about Palantir GothamRed 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.
- Users report that Palantir Gotham excels in Data Ingestion & Wrangling with a score of 8.9, making it easier for teams to prepare and manage their data efficiently. In contrast, Red Hat OpenShift Data Science, while strong, has a slightly lower score in this area, indicating that users may find it less intuitive for initial data handling.
- Reviewers mention that Palantir Gotham's Quality of Support is rated at 9.4, highlighting its responsive and helpful customer service. On the other hand, Red Hat OpenShift Data Science has a lower support rating of 8.6, suggesting that users may experience longer wait times or less comprehensive assistance.
- G2 users indicate that Palantir Gotham shines in Model Development with a score of 8.8, particularly due to its robust pre-built algorithms and feature engineering capabilities. Red Hat OpenShift Data Science, while competitive, has slightly lower scores in these areas, which may affect users looking for advanced model training options.
- Users on G2 highlight that Palantir Gotham offers superior Real-Time Integration capabilities, scoring 8.9, which is crucial for businesses needing immediate data insights. In comparison, Red Hat OpenShift Data Science's integration features, while effective, do not match the immediacy and efficiency of Gotham's offerings.
- Reviewers say that Palantir Gotham's Data Governance features are robust, with a focus on compliance and data protection, scoring 9.4. Red Hat OpenShift Data Science, while it provides essential governance tools, scores lower at 8.5, indicating potential gaps in comprehensive data management.
- Users report that both platforms are strong in Deployment, but Palantir Gotham's managed service score of 8.6 is slightly lower than Red Hat OpenShift Data Science's 8.8, suggesting that users may find OpenShift's deployment options more flexible and user-friendly.
Pricing
Entry-Level Pricing
Palantir Gotham
No pricing availableRed Hat OpenShift Data Science
No pricing availableFree Trial
Palantir Gotham
No trial information availableRed Hat OpenShift Data Science
No trial information availableRatings
Meets Requirements
9.4
6
8.8
23
Ease of Use
9.0
5
8.5
23
Ease of Setup
Not enough data
Not enough data
Ease of Admin
Not enough data
Not enough data
Quality of Support
9.4
6
8.6
21
Has the product been a good partner in doing business?
Not enough data
Not enough data
Product Direction (% positive)
10.0
7
10.0
23
Features by Category
System
Not enough data
8.9
22
Model Development
Not enough data
8.8
23
Not enough data
8.8
23
Not enough data
8.7
23
Not enough data
8.6
23
Model Development
Not enough data
8.8
23
Machine/Deep Learning Services
Not enough data
8.5
22
Not enough data
8.3
20
Not enough data
8.6
20
Not enough data
8.3
20
Machine/Deep Learning Services
Not enough data
8.6
20
Not enough data
8.7
21
Deployment
Not enough data
8.6
22
Not enough data
8.8
22
Not enough data
8.5
22
Generative AI
Not enough data
8.3
5
Not enough data
8.7
5
Not enough data
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
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
Security
Not enough data
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
Development
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
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
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
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
Security
Not enough data
Not enough data
Not enough data
Not enough data
Statistical Tool
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Data Analysis
Not enough data
Not enough data
Not enough data
Not enough data
Decision Making
Not enough data
Not enough data
Not enough data
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
Categories
Categories
Shared Categories
Palantir Gotham and Red Hat OpenShift Data Science are categorized as Data Science and Machine Learning Platforms
Unique Categories
Palantir Gotham is categorized as Master Data Management (MDM), Predictive Analytics, Data Fabric, Big Data Integration Platforms, and iPaaS
Red Hat OpenShift Data Science has no unique categories
Reviews
Reviewers' Company Size
Palantir Gotham
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
Computer Software
37.5%
Transportation/Trucking/Railroad
12.5%
Information Technology and Services
12.5%
Government Relations
12.5%
Airlines/Aviation
12.5%
Other
12.5%
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
Palantir Gotham has no discussions with answers
Red Hat OpenShift Data Science has no discussions with answers
Hunting for software insights?
With over 3 million reviews, we can provide the specific details that help you make an informed software buying decision for your business. Finding the right product is important, let us help.
