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Compare Codefresh and GitLab 
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At a Glance
Market Segments
Small-Business (51.5% of reviews)
Small-Business (37.3% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Codefresh
Star Rating
(70)4.6 out of 5
Market Segments
Small-Business (51.5% of reviews)
Entry-Level Pricing
No pricing available
Learn more about CodefreshGitLab
Star Rating
(860)4.5 out of 5
Market Segments
Small-Business (37.3% of reviews)
Entry-Level Pricing
No pricing available
Free Trial is available
Learn more about GitLabSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that GitLab excels in its Pipeline Control feature, scoring 9.0, which allows for seamless management of CI/CD processes. In contrast, Codefresh also performs well with a score of 9.3, but users mention that its Workflow Visualization is slightly more intuitive, scoring 8.8.
- Reviewers mention that GitLab's Test Automation feature is highly rated at 9.0, providing robust capabilities for automated testing. However, Codefresh users say that its Test Automation feature is even better, with a score of 9.1, highlighting its ease of use and integration with existing workflows.
- G2 users report that GitLab's Documentation is comprehensive and user-friendly, scoring 8.8, which helps in onboarding new users. On the other hand, Codefresh users mention that while its documentation is good, it could be more detailed, reflected in a lower score of 8.6.
- Users on G2 highlight GitLab's Configuration Management feature, which scores 8.8, as a strong point for managing infrastructure as code. In comparison, Codefresh's score of 8.3 indicates that users find it less effective in this area, with some mentioning challenges in managing configurations.
- Reviewers say that GitLab's Quality of Support is rated at 8.5, with many users appreciating the responsiveness of the support team. Conversely, Codefresh users report a similar score of 8.5 but mention that the support is more specialized for CI/CD processes, which can be a deciding factor for teams focused on continuous delivery.
- Users report that GitLab's Extensibility feature scores 8.6, allowing for a wide range of integrations. However, Codefresh shines with a score of 8.1 in this area, with users mentioning that its integrations are more tailored for specific use cases, making it easier to connect with other tools in the DevOps ecosystem.
Pricing
Entry-Level Pricing
Codefresh
No pricing availableGitLab
No pricing availableFree Trial
Codefresh
Free Trial is available
GitLab
Free Trial is available
Ratings
Meets Requirements
8.9
43
9.1
650
Ease of Use
9.2
45
8.7
652
Ease of Setup
8.6
21
8.6
213
Ease of Admin
9.2
21
8.6
170
Quality of Support
8.5
43
8.5
514
Has the product been a good partner in doing business?
8.9
21
8.8
145
Product Direction (% positive)
9.2
42
8.7
617
Features by Category
Administration
Not enough data
8.7
122
Not enough data
8.9
130
7.7
5
8.6
122
Functionality
7.7
5
9.0
128
Not enough data
8.5
114
Not enough data
8.5
109
Not enough data
8.7
114
Not enough data
8.6
103
Processes
Not enough data
9.1
131
Not enough data
9.0
120
Not enough data
8.7
120
Administration
Not enough data
9.1
27
Not enough data
9.0
26
Analysis
Not enough data
8.6
25
Not enough data
8.9
26
Not enough data
9.1
26
Not enough data
8.8
24
Testing
Not enough data
8.8
26
Not enough data
8.7
25
Not enough data
9.1
25
Not enough data
8.8
25
Not enough data
8.8
23
Not enough data
8.4
23
Not enough data
8.7
23
Agentic AI - Static Application Security Testing (SAST)
Not enough data
Not enough data
Administration
Not enough data
9.2
24
Not enough data
8.8
23
Analysis
Not enough data
8.4
23
Not enough data
9.1
23
Not enough data
8.8
23
Not enough data
8.8
23
Not enough data
8.9
23
Testing
Not enough data
8.6
22
Not enough data
9.1
22
Not enough data
8.9
21
Not enough data
9.0
20
Not enough data
8.9
19
Not enough data
9.1
20
Administration
Not enough data
8.7
76
Not enough data
8.7
77
Not enough data
8.7
74
Not enough data
8.8
79
Automation
Not enough data
8.9
78
Not enough data
8.4
71
Not enough data
9.0
78
Not enough data
8.6
72
IT Management
Not enough data
8.7
73
Not enough data
8.8
73
Not enough data
8.6
70
Functionality
8.7
15
8.8
210
8.8
15
9.0
212
8.6
11
8.7
204
Management
8.6
15
8.7
197
7.4
12
8.3
190
9.0
17
8.9
204
Agentic AI - Continuous Delivery
Not enough data
8.0
9
Not enough data
8.2
10
Not enough data
7.5
10
Not enough data
7.5
10
Not enough data
7.2
9
Bug Reporting
Not enough data
8.6
138
Not enough data
8.5
132
Not enough data
8.6
139
Bug Monitoring
Not enough data
8.4
135
Not enough data
8.8
144
Not enough data
8.8
134
Agentic AI - Bug Tracking
Not enough data
8.3
9
Not enough data
7.9
8
Not enough data
8.3
8
Functionality - Software Composition Analysis
Not enough data
8.7
64
Not enough data
8.8
69
Not enough data
8.7
66
Effectiveness - Software Composition Analysis
Not enough data
8.8
63
Not enough data
8.9
63
Not enough data
8.9
60
Management
8.3
6
8.7
140
8.3
6
8.8
145
8.6
6
8.5
133
Functionality
8.9
9
8.8
145
8.6
7
8.8
145
8.6
6
8.7
137
Processes
9.3
7
9.0
149
8.8
7
8.5
138
8.8
8
9.0
152
Functionality
8.5
16
|
Verified
8.9
223
|
Verified
8.1
15
|
Verified
8.6
208
|
Verified
8.1
17
|
Verified
8.4
202
|
Verified
Management
8.6
18
|
Verified
8.8
210
|
Verified
8.9
15
|
Verified
8.7
213
|
Verified
7.9
14
|
Verified
8.4
195
|
Verified
Agentic AI - Continuous Integration
Not enough data
7.0
10
Not enough data
7.4
12
Not enough data
7.6
11
Not enough data
7.3
10
Not enough data
7.7
10
Documentation
Not enough data
8.8
114
Not enough data
8.6
110
Not enough data
8.3
110
Security
Not enough data
8.0
99
Not enough data
8.4
98
Not enough data
8.9
107
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
Support
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - AI Code Generation
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
Value Analysis
Not enough data
8.9
38
Not enough data
8.7
40
Not enough data
8.6
36
Not enough data
8.8
36
Value Management
Not enough data
8.9
38
Not enough data
8.7
40
Not enough data
8.8
39
Categories
Categories
Shared Categories
Codefresh and GitLab are categorized as DevOps Platforms, Application Release Orchestration, Continuous Delivery, Continuous Integration, and Bug Tracking
Unique Categories
Codefresh is categorized as Container Networking and Build Automation
Reviews
Reviewers' Company Size
Codefresh
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
GitLab
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
37.9%
Information Technology and Services
15.2%
Financial Services
7.6%
Marketing and Advertising
6.1%
Education Management
4.5%
Other
28.8%
Computer Software
33.5%
Information Technology and Services
24.1%
Internet
3.9%
Financial Services
3.4%
Telecommunications
2.3%
Other
32.8%
Alternatives
Discussions
How can we speed up a heavy build?
1 Comment
KK
Hello. Codefresh contains several caching mechanisms for both Docker builds and traditional compilation jobs.
Please see the documentation page at...Read more
Is Codefresh open source?
1 Comment
Official Response from Codefresh
The Codefresh platform is largely open source. The Argo Project is the largest open source component of the platform and Codefresh is an official maintainer...Read more
Is Codefresh free?
1 Comment
Official Response from Codefresh
Codefresh has a free tier that provides CI/CD, GitOps orchestration, etc. Community version details are available here https://codefresh.io/pricing/Read more
Is GitLab paid?
5 Comments
PG
Yes, Gitlab is paid as it provides the flexibility to use all the features of the GitHub and Git as well as the freedom to use your own DataBase so that you...Read more
Is GitLab free software?
4 Comments
RB
Yes, in that for non-commercial users, payment is unnecessary. Additionally, its source is publicly available.Read more
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