Compare Cloudera Data Engineering and Databricks 
At a Glance
Market Segments
Mid-Market (39.1% of reviews)
Enterprise (44.6% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Cloudera Data Engineering
Star Rating
(23)4.7 out of 5
Market Segments
Mid-Market (39.1% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about Cloudera Data EngineeringDatabricks
Star Rating
(727)4.6 out of 5
Market Segments
Enterprise (44.6% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about DatabricksSummary
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 and Lakehouse Connect that streamline data processing and analysis. Users appreciate the all-in-one platform that reduces the need to switch between multiple tools.
- Users say Cloudera Data Engineering offers a robust environment for building and managing data pipelines, particularly highlighting its integration with Apache Spark and Airflow. This makes batch processing and scheduling efficient, which is a significant advantage for teams focused on automation.
- Reviewers mention that Databricks has a higher overall satisfaction score, reflecting its strong performance in user experience and support. The recent feedback emphasizes the value of Unity Catalog for centralized governance and fine-grained access control, which has been a game-changer for enterprise migrations.
- According to verified reviews, Cloudera Data Engineering shines in ease of use and setup, with users noting that the platform is straightforward to navigate and implement. This is particularly beneficial for teams looking to quickly establish their data operations without extensive training.
- G2 reviewers highlight that while Databricks has a wealth of features, some users feel it may not fully meet their specific workflow needs, occasionally leading to configuration challenges. This contrasts with Cloudera's more tailored approach to data pipeline management.
- Users report that Databricks' recent updates and features, such as streaming tables, significantly enhance its capabilities, but they also note that Cloudera Data Engineering's focus on historical and stream data processing provides a solid foundation for analytics, making it a strong contender for data-centric organizations.
Pricing
Entry-Level Pricing
Cloudera Data Engineering
No pricing availableDatabricks
No pricing availableFree Trial
Cloudera Data Engineering
No trial information availableDatabricks
Free Trial is available
Ratings
Meets Requirements
9.2
23
8.9
578
Ease of Use
9.3
23
8.9
589
Ease of Setup
9.8
7
8.7
461
Ease of Admin
9.5
7
8.4
184
Quality of Support
9.2
22
8.7
553
Has the product been a good partner in doing business?
9.3
7
8.9
188
Product Direction (% positive)
10.0
23
9.6
566
Features by Category
Reports
Not enough data
8.3
12
Not enough data
7.7
10
Not enough data
8.3
11
Not enough data
8.0
9
Not enough data
9.0
15
Data Preparation
Not enough data
8.9
6
Not enough data
8.8
7
Data Modeling and Blending
Not enough data
9.0
8
Not enough data
8.8
7
Not enough data
8.8
8
Generative AI
Not enough data
9.1
9
Not enough data
9.2
6
Agentic AI - Analytics Platforms
Not enough data
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
Self Service
Not enough data
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
Deployment & Integration - Analytics Platforms
Not enough data
8.1
7
Not enough data
9.2
8
Not enough data
8.6
6
Not enough data
9.2
6
Advanced Analytics
Not enough data
8.3
11
Not enough data
8.2
11
Not enough data
9.0
12
Performance & Scalability - Analytics Platforms
Not enough data
8.8
7
Not enough data
Not enough data
Advanced Analytics & Modeling - Analytics Platforms
Not enough data
9.0
8
Not enough data
8.5
8
Not enough data
8.6
6
Agentic AI Capabilities - Analytics Platforms
Not enough data
8.6
7
Not enough data
8.8
7
Not enough data
8.9
6
Not enough data
8.6
7
Personalized Intelligence - Analytics Platforms
Not enough data
9.2
6
Not enough data
7.9
8
Not enough data
8.3
7
Building Reports
Not enough data
9.0
149
Not enough data
8.6
143
Not enough data
7.6
123
Not enough data
8.4
145
Administration
Not enough data
8.8
99
Not enough data
8.6
93
Not enough data
9.0
94
Not enough data
8.7
98
Management
Not enough data
8.4
87
Not enough data
8.6
86
Not enough data
8.6
88
Not enough data
8.5
87
Not enough data
8.8
86
Compliance
Not enough data
8.8
98
Not enough data
8.7
92
Not enough data
8.9
94
Not enough data
8.7
94
Security
Not enough data
9.0
87
Not enough data
8.9
86
Not enough data
8.8
86
Data Quality
Not enough data
9.0
94
Not enough data
8.7
93
Not enough data
9.0
93
Maintainence
Not enough data
8.7
85
Not enough data
8.8
84
Generative AI
Not enough data
8.4
82
Not enough data
8.5
81
Agentic AI - Data Governance
Not enough data
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
Management
Not enough data
8.6
171
Not enough data
8.5
164
Functionality
Not enough data
9.1
174
Not enough data
9.2
175
Not enough data
9.1
172
Not enough data
9.0
167
Not enough data
9.1
167
Deployment
Not enough data
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
Deployment
Not enough data
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
Management
Not enough data
9.0
64
Not enough data
8.8
65
Not enough data
9.2
61
Not enough data
9.0
69
Operations
Not enough data
8.7
62
Not enough data
8.8
62
Not enough data
9.0
63
Management
Not enough data
8.8
61
Not enough data
8.7
61
Not enough data
9.1
59
Generative AI
Not enough data
8.3
28
Not enough data
8.3
28
System
9.5
16
8.9
180
Model Development
9.8
16
8.8
182
9.3
17
7.9
187
9.2
15
8.3
186
9.3
16
8.7
191
Model Development
9.2
15
8.5
172
Machine/Deep Learning Services
9.2
16
8.2
174
9.4
16
8.5
180
9.3
16
8.3
172
9.2
16
8.2
172
Machine/Deep Learning Services
9.6
15
8.4
158
9.6
14
8.4
160
Deployment
9.3
16
8.5
178
9.5
17
8.7
180
9.4
16
9.0
187
Generative AI
9.4
14
8.2
86
9.0
14
8.4
87
9.1
15
7.6
86
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
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
Data Management
Not enough data
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
Integration
Not enough data
8.8
168
|
Verified
Not enough data
8.8
166
|
Verified
Not enough data
9.1
174
|
Verified
Deployment
Not enough data
7.9
156
|
Verified
Not enough data
9.1
178
|
Verified
Performance
Not enough data
9.1
177
|
Verified
Security
Not enough data
8.8
168
|
Verified
Not enough data
8.9
168
|
Verified
Generative AI
Not enough data
8.5
76
Not enough data
8.4
75
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
Not enough data
9.0
68
Not enough data
8.8
70
Not enough data
8.8
68
Not enough data
9.1
69
Agentic AI - DataOps Platforms
Not enough data
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
Analytics
Not enough data
8.8
67
Not enough data
8.5
67
Monitoring and Management
Not enough data
8.6
67
Not enough data
8.6
68
Cloud Deployment
Not enough data
9.0
63
Not enough data
9.0
64
Generative AI
Not enough data
8.9
36
Not enough data
8.9
36
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
Not enough data
8.7
237
Not enough data
8.9
244
Not enough data
9.3
259
Integrations
Not enough data
8.3
220
Not enough data
9.1
261
Platform
Not enough data
9.0
252
Not enough data
8.8
249
Not enough data
9.1
261
Processing
Not enough data
9.0
244
Not enough data
9.0
246
Data Transformation
Not enough data
8.8
226
Not enough data
9.1
233
Connectivity
Not enough data
8.7
206
Not enough data
9.2
230
Not enough data
9.0
220
Not enough data
9.2
230
Operations
Not enough data
8.4
228
Not enough data
8.8
224
Not enough data
8.6
212
Not enough data
8.6
209
Not enough data
9.3
231
Building Reports
Not enough data
9.0
149
Not enough data
8.6
143
Not enough data
7.6
123
Not enough data
8.4
145
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
Cloudera Data Engineering and Databricks are categorized as Data Science and Machine Learning Platforms
Unique Categories
Cloudera Data Engineering has no unique categories
Reviews
Reviewers' Company Size
Cloudera Data Engineering
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Databricks
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
26.1%
Computer Software
26.1%
Consulting
13.0%
Banking
8.7%
Program Development
4.3%
Other
21.7%
Information Technology and Services
15.9%
Financial Services
10.4%
Computer Software
8.5%
Consulting
4.0%
Hospital & Health Care
3.7%
Other
57.5%
Alternatives
Discussions
Cloudera Data Engineering has no discussions with answers
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
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