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Digital.ai Release vs Microsoft Azure DevOps comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 7, 2025

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Digital.ai Release
Ranking in Release Automation
10th
Average Rating
8.4
Reviews Sentiment
7.5
Number of Reviews
5
Ranking in other categories
Build Automation (15th), DevSecOps (7th)
Microsoft Azure DevOps
Ranking in Release Automation
1st
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
137
Ranking in other categories
Application Lifecycle Management (ALM) Suites (2nd), Enterprise Agile Planning Tools (1st)
 

Mindshare comparison

As of January 2026, in the Release Automation category, the mindshare of Digital.ai Release is 1.2%, up from 0.7% compared to the previous year. The mindshare of Microsoft Azure DevOps is 31.1%, down from 38.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Release Automation Market Share Distribution
ProductMarket Share (%)
Microsoft Azure DevOps31.1%
Digital.ai Release1.2%
Other67.69999999999999%
Release Automation
 

Featured Reviews

Jeanne-Mari Chandran - PeerSpot reviewer
Software Configuration Specialist at a insurance company with 10,001+ employees
Experience seamless project management and integration with robust tools
The features I find most valuable in Digital.ai Release are the integration with MS Teams, because we have MS Teams channels that publish or push notifications to that. When we start deployments, it sends a notification to the people that we are doing a deployment to their environment. It notifies them when the deployment is started, completed, or if attention is required. I also appreciate the fact that it has plugins for Bamboo and I use lots of Gradle and JSON scripts, and we do SQL upgrades as well, triggering Flyway scripts via Bamboo, along with the integration with XLD and Jira; it's all Atlassian software. Regarding environment management capabilities, Digital.ai Release is mostly useful for me, as it is more application related and that is managed via my XLD dictionary. We have one artifact that is environment agnostic, which has placeholders that correspond to my XLD keys and values, and at deployment time, it substitutes the placeholders with those environment specific values. We don't need to make a specific deployment artifact for dev, test, or production; it is all the same artifact using environment variables, ensuring what we take to production is what was tested.
Bharadwaj Deepak Mohapatra - PeerSpot reviewer
DevOps Engineer at ENTERPRISE SYSTEM SOLUTIONS LIMITED
Have built reliable end-to-end pipelines and streamlined cloud provisioning through consistent collaboration practices
I am currently working with open-source tools such as Jenkins for my main CI/CD pipeline, and for enterprise clients, I am using Microsoft Azure DevOps CI/CD pipeline. For other clients, I have also implemented CI/CD YAML pipelines through GitLab CI/CD workflow and GitHub Actions. I am creating the end-to-end CI/CD pipeline from development to deployment and monitoring all of this. Azure Boards is easier than Jira for my understanding because there are very easy points to manage the Agile methodology which we work on. Because it is a GUI, sometimes the process may take a few minutes more than the CLI process since the backend is running the exact CLI, but we are commanding through the GUI. There is definitely a time lag, but it is more secure. Microsoft Azure DevOps pipelines work very seamlessly rather than other CI/CD pipelines, as of my understanding. The downside is that the process may take more time when deploying some clusters, Kubernetes, Azure AKS service, or some vast microservice architecture deployments. There may be a little bit of lag I feel, though I cannot tell very strictly that this is a disadvantage, but sometimes it takes a little more time than other cloud infrastructures. All the major things are done by GUI, which is somewhat a little slow. However, if considering automations, process, monitoring, and provisioning, then it is the best cloud service across all the other service providers. Our implementation is a hybrid cloud. Microsoft Azure DevOps is definitely easily scalable. I have worked on many Kubernetes infrastructures and microservice deployments, and I have seen that replication is very good because it is very easy. The replication process is very straightforward. I definitely advocate for using less code because it is very time-consuming. If using GCP or Amazon Web Service, there is more interaction related to work over the CLI process. In terms of Microsoft Azure DevOps, there are many things done by the GUI, which is the best part.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The most valuable feature of Digital.ai Release is its ability to communicate with various deployment systems, such as XLD and batch deployments, as well as integrate with tools, such as Flyway and Bamboo. We use Bamboo as our build orchestrator, and Digital.ai Release also integrates with Jira, another Atlassian solution. These capabilities make it a powerful tool for managing workflow, test automation, and other processes."
"The solution can apply one template across multiple applications."
"Overall, I would give Digital.ai Release a rating of nine out of ten; there's always room for improvement, but it's really good."
"The time is also reduced because the manual work has tremendously decreased. We just have to click one button, and it will create everything for us."
"The orchestration, building the release, and then just executing it and managing that pipeline — the orchestration capabilities are great for that."
"The work items option is incredibly flexible."
"The solution is scalable."
"Version control practices have been perfect for us. It maintains a detailed history and is integrated with GitHub, which is also a Microsoft product. It is quite a game-changer."
"The reports have been most valuable. We have created some dashboards allowing us to be able to check our teams, their progress, and mission plans."
"The pricing seems to be reasonable."
"This solution is stable."
"Provides agile management of projects."
"The extensibility of the work item forms and customizations as well as the backend API to query the data, et cetera, and manipulate the data programmatically are all very valuable aspects of the product."
 

Cons

"Digital.ai Release could improve by having a better plugin that works with Guardian that we use for mainframe migrations. If there could be an interface or plugin for Guardian that would be beneficial."
"I would like to improve Digital.ai Release by exploring its cloud capabilities as we are currently in the middle of migrating to the cloud, but I actually have no idea what Digital.ai's cloud capabilities are."
"The backfill could be improved, we could automate that. Right now it's subjective — it's up to the lead developer's memory to remember to backfill."
"Currently, we put artifact details manually. What we could improve, in our case, is the deployment instruction base. Developers input all the information, including which artifact and where it needs to be deployed. What Digital.ai could do is automatically go to the deployment instruction page, take those artifact details, and implement them."
"The solution is a little bit expensive."
"The installation time of this solution depends on the environment it is being implemented in. We had a couple of projects that took around two weeks of implementation. This included the whole integration of the DevOps and everything together."
"The testing environment and different pipelining concepts can be improved."
"Something that could be improved is the initial setup with the integration of ReadyAPI."
"Another area is the Azure monitoring agent for Citrix machines. There's room for improvement there too."
"Improvements can be made mostly on the team management aspects."
"There is room for improvement on the UI side, especially with merge requests. If we compare Azure DevOps to GitLab when it comes to branches and PRs (pull requests), GitLab has a better interface."
"The tool was developed for Agile project methodology, but I've noticed that there has also been a try to incorporate what is typically done in MS Project, which is for more sequential Waterfall projects. The problem with that is that it is half-baked for Waterfall projects. If you're going to do it, then either go all the way and allow us to use the tool for both or don't do it at all."
"Project management could be improved."
 

Pricing and Cost Advice

"Overall, the price is just too high; especially considering we're in the middle of a pandemic."
"The solution's license includes all features."
"There is a license for this solution."
"It is the least expensive product in this class."
"With Azure, you have to pay for every user."
"It's a good tool, quite rich, it has a lot of features, and quite a lot of analytical capabilities which are built on top of it so that you can see how your projects are going and all that stuff. It's a good tool."
"Its pricing is reasonable for the number of features that you get and the functionality that you can utilize for the agile delivery, which is what we are using it for. I found it extremely cost-effective."
"We do not pay licenses for this solution."
"The licensing costs are reasonable."
"The price is cheaper than Jira and some of the other competing tools."
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Top Industries

By visitors reading reviews
Financial Services Firm
29%
Computer Software Company
11%
Insurance Company
11%
Healthcare Company
10%
Manufacturing Company
14%
Government
10%
Financial Services Firm
10%
Computer Software Company
10%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business42
Midsize Enterprise28
Large Enterprise69
 

Questions from the Community

What do you like most about Digital.ai Release ?
The time is also reduced because the manual work has tremendously decreased. We just have to click one button, and it will create everything for us.
What needs improvement with Digital.ai Release ?
Based on my experience, I would like to improve Digital.ai Release by exploring its cloud capabilities as we are currently in the middle of migrating to the cloud, but I actually have no idea what ...
What is your primary use case for Digital.ai Release ?
My use case for Digital.ai Release is that I work for an insurance company on a very big project that develops multiple different pieces of software. We use Digital.ai Release to move our software ...
Which is better - Jira or Microsoft Azure DevOps?
Jira is a great centralized tool for just about everything, from local team management to keeping track of products and work logs. It is easy to implement and navigate, and it is stable and scalabl...
Which is better - TFS or Azure DevOps?
TFS and Azure DevOps are different in many ways. TFS was designed for admins, and only offers incremental improvements. In addition, TFS seems complicated to use and I don’t think it has a very fri...
What do you like most about Microsoft Azure DevOps?
Valuable features for project management and tracking in Azure DevOps include a portal displaying test results, check-in/check-out activity, and developer/tester productivity.
 

Also Known As

XL Release, XebiaLabs XL Release
Azure DevOps, VSTS, Visual Studio Team Services, MS Azure DevOps
 

Overview

 

Sample Customers

3M, GE, John Deere, Deutsche Telekom, Cable & Wireless, Xerox, and Société Générale, Liberty Mutual, EA, Rabobank
Alaska Airlines, Iberia Airlines, Columbia, Skype
Find out what your peers are saying about Digital.ai Release vs. Microsoft Azure DevOps and other solutions. Updated: December 2025.
881,082 professionals have used our research since 2012.