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Digital.ai Release vs Tekton comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Mar 5, 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 Build Automation
15th
Average Rating
8.4
Reviews Sentiment
7.5
Number of Reviews
5
Ranking in other categories
Release Automation (10th), DevSecOps (7th)
Tekton
Ranking in Build Automation
2nd
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
37
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of February 2026, in the Build Automation category, the mindshare of Digital.ai Release is 2.0%, up from 0.8% compared to the previous year. The mindshare of Tekton is 7.0%, down from 12.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Build Automation Market Share Distribution
ProductMarket Share (%)
Tekton7.0%
Digital.ai Release2.0%
Other91.0%
Build 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.
reviewer2741265 - PeerSpot reviewer
Software engineer at a manufacturing company with 10,001+ employees
Benefit from a smooth learning curve and efficient adaptability
After seeing Jenkins and Tekton, I think Tekton is quite built on top of Kubernetes, so the learning curve is minimal. If you are working with Kubernetes, then OpenShift created Tekton on top of that, making it easily adaptable. Tekton is highly customizable. With Kubernetes, we can customize on our own and create custom builders. If teams have time and want to make enhancements, they can do it themselves. Whatever OpenShift is providing regarding Tekton is sufficient. It is easy to use because we don't need to write every pod step every time. A proper DevOps engineer can help once or twice, and development teams can easily adapt to that, make small shell script changes in the steps, understand the process, and work with it.

Quotes from Members

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

Pros

"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 solution can apply one template across multiple applications."
"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 orchestration, building the release, and then just executing it and managing that pipeline — the orchestration capabilities are great for that."
"Tekton's most important feature is its cloud-native nature. Unlike Jenkins, which may not scale as efficiently, Tekton's CI pipeline can automatically scale up to handle increased workload demands without needing manual adjustments."
"Tekton has a user interface that facilitates time savings, making it more user-friendly than Jenkins."
"It enables enterprises to build a flexible framework atop Tekton, making it easier to define workflows with standard inputs and outputs."
"You can isolate most Tekton assets in the Kubernetes namespace for your feature branch. This allows you to freely change Tekton assets and objects to adapt to your feature branch and requirements."
"It is an open-source tool, which makes it highly adaptable."
"Tekton's inclusion in Kubernetes deployment offers better visibility on how Tekton is performing within a cluster. It is lightweight and not as heavy as Jenkins to maintain."
"Its seamless integration with Kubernetes, being built on top of it and utilizing Custom Resource Definitions, ensures a smooth experience within Kubernetes environments exclusively."
"I like the setup of the dashboard."
 

Cons

"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."
"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."
"The solution is a little bit expensive."
"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."
"There might be occasional issues with storage or cluster-level logging, which can affect production."
"If you are a beginner, then accessing the flexibility part can be overwhelming. We think the learning curve of the tool is steep, especially for those who are not already familiar with Kubernetes."
"RBAC is really needed for Tekton."
"Initially, working with YAML configuration can be challenging using the solution."
"It would be better if Tekton could show the YAML file while it is running, similar to GitHub pipelines, to provide more visibility on what's happening."
"It would be beneficial to find case studies or more information on complex implementations."
"Tekton lacks integration capabilities compared to other CI/CD tools like Jenkins and Travis."
"The product's documentation is an area of concern, making it an area where improvements are required."
 

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."
"The product is free and open-source."
"The tool is open-source and free to use."
"It is entirely open source and free of charge."
"Tekton is an open-source tool."
"The product is free of cost."
"The solution is open-source."
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Top Industries

By visitors reading reviews
Financial Services Firm
26%
Computer Software Company
12%
Insurance Company
12%
Healthcare Company
10%
Financial Services Firm
22%
Manufacturing Company
11%
Computer Software Company
8%
Government
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business11
Midsize Enterprise4
Large Enterprise22
 

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 ...
How does Tekton compare with Jenkins?
When you are evaluating tools for automating your own GitOps-based CI/CD workflow, it is important to keep your requirements and use cases in mind. Tekton deployment is complex and it is not very e...
What needs improvement with Tekton?
I didn't get the intention of scalability. Scalability means based on the load, it will automatically gain resources and run. The question of pipeline scalability remains unclear. It's quite easy t...
What is your primary use case for Tekton?
We use Tekton for build and deployments. For LMP testing, we use the Tekton pipeline. We also use GitHub CI/CD. For infrastructure pipelines and Infrastructure as Code (IaC), we use Tekton. Previou...
 

Comparisons

 

Also Known As

XL Release, XebiaLabs XL Release
No data available
 

Overview

 

Sample Customers

3M, GE, John Deere, Deutsche Telekom, Cable & Wireless, Xerox, and Société Générale, Liberty Mutual, EA, Rabobank
The Home Depot, PayPal, Target, HSBC, McKesson, Oncology Venture
Find out what your peers are saying about Digital.ai Release vs. Tekton and other solutions. Updated: February 2026.
881,733 professionals have used our research since 2012.