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Compare GitLab and IBM DevOps Deploy 
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At a Glance
Market Segments
Small-Business (37.3% of reviews)
Enterprise (100.0% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
GitLab
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 GitLabIBM DevOps Deploy
Star Rating
(17)4.4 out of 5
Market Segments
Enterprise (100.0% of reviews)
Entry-Level Pricing
No pricing available
Learn more about IBM DevOps DeploySummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that IBM UrbanCode Deploy excels in Deployment Automation with a score of 9.0, highlighting its ability to streamline complex deployment processes effectively. In contrast, GitLab also performs well in this area but scores slightly lower at 8.8, indicating that while it is capable, it may not be as robust for large-scale deployments.
- Reviewers mention that IBM UrbanCode Deploy's Configuration Management feature is rated at 8.8, which users appreciate for its comprehensive control over application configurations. GitLab, while also strong in this area with a score of 8.8, is noted for its integration capabilities, which some users feel can complicate the management process.
- G2 users highlight the API / Integrations capabilities of IBM UrbanCode Deploy, scoring 9.2, as a standout feature that allows for seamless integration with other tools. GitLab's API / Integrations score of 8.8 is still commendable, but users report that it may require more manual setup compared to UrbanCode's more automated approach.
- Reviewers mention that the Quality of Support for GitLab is rated at 8.5, with many users praising the responsiveness and helpfulness of the support team. In comparison, IBM UrbanCode Deploy's support score of 7.9 is seen as less favorable, with some users expressing a desire for quicker resolution times.
- Users on G2 report that GitLab shines in Testing capabilities, particularly in Test Automation with a score of 9.1, which many find beneficial for continuous integration workflows. IBM UrbanCode Deploy, while effective, scores slightly lower at 9.0, indicating it may not offer the same level of automation in testing scenarios.
- Reviewers mention that both products have strong Extensibility features, but IBM UrbanCode Deploy scores 9.0, which users appreciate for its flexibility in adapting to various environments. GitLab's extensibility score of 8.6 is still good, but some users feel it lacks the same level of customization options as UrbanCode.
Pricing
Entry-Level Pricing
GitLab
No pricing availableIBM DevOps Deploy
No pricing availableFree Trial
GitLab
Free Trial is available
IBM DevOps Deploy
No trial information availableRatings
Meets Requirements
9.1
650
8.8
11
Ease of Use
8.7
652
8.9
11
Ease of Setup
8.6
213
7.8
6
Ease of Admin
8.6
170
7.8
6
Quality of Support
8.5
514
7.9
11
Has the product been a good partner in doing business?
8.8
145
8.1
6
Product Direction (% positive)
8.7
617
7.9
11
Features by Category
Administration
8.7
122
Not enough data
8.9
130
Not enough data
8.6
122
Not enough data
Functionality
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
Not enough data
Processes
9.1
131
Not enough data
9.0
120
Not enough data
8.7
120
Not enough data
Administration
9.1
27
Not enough data
9.0
26
Not enough data
Analysis
8.6
25
Not enough data
8.9
26
Not enough data
9.1
26
Not enough data
8.8
24
Not enough data
Testing
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
Not enough data
Agentic AI - Static Application Security Testing (SAST)
Not enough data
Not enough data
Administration
9.2
24
Not enough data
8.8
23
Not enough data
Analysis
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
Not enough data
Testing
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
Not enough data
Administration
8.7
76
Not enough data
8.7
77
Not enough data
8.7
74
Not enough data
8.8
79
Not enough data
Automation
8.9
78
Not enough data
8.4
71
Not enough data
9.0
78
Not enough data
8.6
72
Not enough data
IT Management
8.7
73
Not enough data
8.8
73
Not enough data
8.6
70
Not enough data
Functionality
8.8
210
Not enough data
9.0
212
Not enough data
8.7
204
Not enough data
Management
8.7
197
Not enough data
8.3
190
Not enough data
8.9
204
Not enough data
Agentic AI - Continuous Delivery
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
Not enough data
Bug Reporting
8.6
138
Not enough data
8.5
132
Not enough data
8.6
139
Not enough data
Bug Monitoring
8.4
135
Not enough data
8.8
144
Not enough data
8.8
134
Not enough data
Agentic AI - Bug Tracking
8.3
9
Not enough data
7.9
8
Not enough data
8.3
8
Not enough data
Functionality - Software Composition Analysis
8.7
64
Not enough data
8.8
69
Not enough data
8.7
66
Not enough data
Effectiveness - Software Composition Analysis
8.8
63
Not enough data
8.9
63
Not enough data
8.9
60
Not enough data
Management
8.7
140
Not enough data
8.8
145
Not enough data
8.5
133
Not enough data
Functionality
8.8
145
Not enough data
8.8
145
Not enough data
8.7
137
Not enough data
Processes
9.0
149
Not enough data
8.5
138
Not enough data
9.0
152
Not enough data
Functionality
8.9
223
|
Verified
Not enough data
8.6
208
|
Verified
Not enough data
8.4
202
|
Verified
Not enough data
Management
8.8
210
|
Verified
Not enough data
8.7
213
|
Verified
Not enough data
8.4
195
|
Verified
Not enough data
Agentic AI - Continuous Integration
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
Not enough data
Documentation
8.8
114
Not enough data
8.6
110
Not enough data
8.3
110
Not enough data
Security
8.0
99
Not enough data
8.4
98
Not enough data
8.9
107
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
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
8.9
38
Not enough data
8.7
40
Not enough data
8.6
36
Not enough data
8.8
36
Not enough data
Value Management
8.9
38
Not enough data
8.7
40
Not enough data
8.8
39
Not enough data
Categories
Categories
Shared Categories
GitLab and IBM DevOps Deploy are categorized as Continuous Delivery
Unique Categories
GitLab is categorized as Secure Code Review, DevOps Platforms, Value Stream Management, Software Composition Analysis, Cloud Infrastructure Automation, Dynamic Application Security Testing (DAST), Static Application Security Testing (SAST), Application Release Orchestration, Version Control Hosting, Peer Code Review, Bug Tracking, Continuous Integration, and AI Code Generation
IBM DevOps Deploy has no unique categories
Reviews
Reviewers' Company Size
GitLab
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
IBM DevOps Deploy
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
33.5%
Information Technology and Services
24.1%
Internet
3.9%
Financial Services
3.4%
Telecommunications
2.3%
Other
32.8%
Insurance
26.7%
Information Technology and Services
20.0%
Financial Services
20.0%
Banking
13.3%
Retail
6.7%
Other
13.3%
Alternatives
Discussions
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
IBM DevOps Deploy has no discussions with answers
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