Compare Databricks and NVIDIA CUDA GL 
At a Glance
Market Segments
Enterprise (45.1% of reviews)
Small-Business (61.5% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Databricks
Star Rating
(711)4.6 out of 5
Market Segments
Enterprise (45.1% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about DatabricksNVIDIA CUDA GL
Star Rating
(39)4.4 out of 5
Market Segments
Small-Business (61.5% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about NVIDIA CUDA GLSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that the Databricks Data Intelligence Platform excels in user satisfaction, boasting a significantly higher overall score compared to NVIDIA CUDA GL. Users appreciate its ability to scale large language models and manage data across multiple cloud environments seamlessly.
- Users say that Databricks offers a more intuitive interface, particularly highlighting its interactive notebooks that support both SQL and Python for data visualization. In contrast, while NVIDIA CUDA GL is praised for its performance in specific tasks like image processing, it lacks the same level of user-friendly features.
- Reviewers mention that the autoscaling feature in Databricks is a game-changer, helping teams optimize cloud resource costs effectively. This capability is often noted as a significant advantage over NVIDIA CUDA GL, which, while powerful, does not provide similar cost management features.
- According to verified reviews, the quality of support for Databricks is frequently highlighted as a strong point, with users noting timely assistance. In comparison, while NVIDIA CUDA GL has its strengths, it does not receive the same level of support feedback, which can be crucial for users needing quick resolutions.
- G2 reviewers indicate that Databricks is particularly well-suited for enterprise-level applications, with a majority of its reviews coming from larger organizations. On the other hand, NVIDIA CUDA GL tends to attract small business users, which may limit its scalability for larger projects.
- Users report that while NVIDIA CUDA GL enhances computing performance through GPU utilization, it may not be as versatile as Databricks for broader data science applications. Databricks users benefit from a comprehensive platform that integrates various tools and functionalities, making it a more holistic choice for data-driven projects.
Pricing
Entry-Level Pricing
Databricks
No pricing availableNVIDIA CUDA GL
No pricing availableFree Trial
Databricks
Free Trial is available
NVIDIA CUDA GL
No trial information availableRatings
Meets Requirements
8.9
567
9.0
30
Ease of Use
8.9
578
7.7
30
Ease of Setup
8.7
450
Not enough data
Ease of Admin
8.3
181
Not enough data
Quality of Support
8.7
542
8.3
27
Has the product been a good partner in doing business?
8.9
185
Not enough data
Product Direction (% positive)
9.6
555
5.4
28
Features by Category
Reports
8.2
11
Not enough data
7.4
9
Not enough data
8.3
11
Not enough data
8.0
9
Not enough data
8.9
14
Not enough data
Data Preparation
8.9
6
Not enough data
8.8
7
Not enough data
Data Modeling and Blending
9.0
8
Not enough data
8.8
7
Not enough data
8.8
8
Not enough data
Generative AI
9.1
9
Not enough data
9.2
6
Not enough data
Agentic AI - Analytics Platforms
9.3
7
Not enough data
8.7
5
Not enough data
8.3
6
Not enough data
8.3
6
Not enough data
8.3
7
Not enough data
9.7
6
Not enough data
9.3
5
Not enough data
Self Service
7.7
10
Not enough data
7.7
10
Not enough data
8.5
11
Not enough data
8.1
12
Not enough data
8.2
11
Not enough data
7.9
8
Not enough data
Deployment & Integration - Analytics Platforms
8.1
7
Not enough data
9.2
8
Not enough data
8.6
6
Not enough data
9.2
6
Not enough data
Advanced Analytics
8.3
11
Not enough data
8.2
11
Not enough data
9.0
12
Not enough data
Performance & Scalability - Analytics Platforms
8.8
7
Not enough data
Not enough data
Not enough data
Advanced Analytics & Modeling - Analytics Platforms
9.0
8
Not enough data
8.5
8
Not enough data
8.6
6
Not enough data
Agentic AI Capabilities - Analytics Platforms
8.6
7
Not enough data
8.8
7
Not enough data
8.9
6
Not enough data
8.6
7
Not enough data
Personalized Intelligence - Analytics Platforms
9.2
6
Not enough data
7.9
8
Not enough data
8.3
7
Not enough data
Building Reports
9.0
148
Not enough data
8.6
143
Not enough data
7.6
123
Not enough data
8.4
144
Not enough data
Administration
8.8
99
Not enough data
8.6
93
Not enough data
9.0
94
Not enough data
8.7
97
Not enough data
Management
8.4
87
Not enough data
8.6
86
Not enough data
8.6
87
Not enough data
8.5
87
Not enough data
8.8
86
Not enough data
Compliance
8.8
98
Not enough data
8.7
92
Not enough data
8.9
94
Not enough data
8.7
94
Not enough data
Security
9.0
86
Not enough data
8.9
85
Not enough data
8.8
86
Not enough data
Data Quality
9.0
94
Not enough data
8.7
93
Not enough data
9.0
93
Not enough data
Maintainence
8.7
85
Not enough data
8.8
83
Not enough data
Generative AI
8.4
82
Not enough data
8.5
81
Not enough data
Agentic AI - Data Governance
8.5
10
Not enough data
8.8
11
Not enough data
9.0
14
Not enough data
8.5
12
Not enough data
9.0
12
Not enough data
9.0
13
Not enough data
Management
8.6
171
Not enough data
8.5
164
Not enough data
Functionality
9.1
172
Not enough data
9.2
174
Not enough data
9.1
172
Not enough data
9.0
167
Not enough data
9.1
167
Not enough data
Deployment
8.9
64
Not enough data
8.9
64
Not enough data
8.9
66
Not enough data
8.9
66
Not enough data
9.0
67
Not enough data
Deployment
8.9
61
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
63
Not enough data
8.8
65
Not enough data
9.2
61
Not enough data
8.9
68
Not enough data
Operations
8.7
62
Not enough data
8.8
61
Not enough data
9.0
62
Not enough data
Management
8.8
60
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
180
Not enough data
Model Development
8.8
182
Not enough data
7.9
187
Not enough data
8.3
186
Not enough data
8.7
190
Not enough data
Model Development
8.5
172
Not enough data
Machine/Deep Learning Services
8.2
174
Not enough data
8.5
180
Not enough data
8.3
172
Not enough data
8.2
172
Not enough data
Machine/Deep Learning Services
8.4
158
Not enough data
8.4
160
Not enough data
Deployment
8.5
178
Not enough data
8.7
180
Not enough data
9.0
187
Not enough data
Generative AI
8.2
86
Not enough data
8.4
87
Not enough data
7.6
86
Not enough data
Agentic AI - Data Science and Machine Learning Platforms
9.2
8
Not enough data
8.3
7
Not enough data
8.1
8
Not enough data
8.6
7
Not enough data
9.2
10
Not enough data
9.2
6
Not enough data
9.3
7
Not enough data
Data Management
9.0
185
|
Verified
Not enough data
8.9
180
|
Verified
Not enough data
8.9
179
|
Verified
Not enough data
8.8
180
|
Verified
Not enough data
8.7
167
|
Verified
Not enough data
9.1
171
|
Verified
Not enough data
Integration
8.8
168
|
Verified
Not enough data
8.8
166
|
Verified
Not enough data
9.1
174
|
Verified
Not enough data
Deployment
7.9
156
|
Verified
Not enough data
9.1
178
|
Verified
Not enough data
Performance
9.1
177
|
Verified
Not enough data
Security
8.8
168
|
Verified
Not enough data
8.9
168
|
Verified
Not enough data
Generative AI
8.5
76
Not enough data
8.4
75
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
68
Not enough data
8.7
69
Not enough data
8.8
68
Not enough data
9.1
68
Not enough data
Agentic AI - DataOps Platforms
9.1
9
Not enough data
8.8
7
Not enough data
8.9
9
Not enough data
9.0
8
Not enough data
9.4
8
Not enough data
Analytics
8.8
67
Not enough data
8.5
67
Not enough data
Monitoring and Management
8.6
67
Not enough data
8.6
68
Not enough data
Cloud Deployment
9.0
63
Not enough data
9.0
64
Not enough data
Generative AI
8.9
36
Not enough data
8.9
36
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
236
Not enough data
8.9
243
Not enough data
9.3
256
Not enough data
Integrations
8.3
220
Not enough data
9.1
256
Not enough data
Platform
9.0
246
Not enough data
8.8
246
Not enough data
9.1
256
Not enough data
Processing
9.0
242
Not enough data
9.0
242
Not enough data
Data Transformation
8.8
226
Not enough data
9.1
232
Not enough data
Connectivity
8.7
206
Not enough data
9.2
230
Not enough data
9.0
220
Not enough data
9.2
230
Not enough data
Operations
8.4
227
Not enough data
8.8
224
Not enough data
8.6
212
Not enough data
8.6
209
Not enough data
9.3
229
Not enough data
Building Reports
9.0
148
Not enough data
8.6
143
Not enough data
7.6
123
Not enough data
8.4
144
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 NVIDIA CUDA GL are categorized as Data Science and Machine Learning Platforms
Reviews
Reviewers' Company Size
Databricks
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
NVIDIA CUDA GL
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
15.4%
Financial Services
10.6%
Computer Software
8.5%
Consulting
3.7%
Hospital & Health Care
3.7%
Other
57.9%
Computer Software
23.1%
Information Technology and Services
10.3%
Accounting
7.7%
Research
7.7%
Airlines/Aviation
5.1%
Other
46.2%
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?
4 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
NVIDIA CUDA GL has no discussions with answers
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