DataKitchen DataOps Platform vs. GitLab

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
DataKitchen DataOps Platform
Score 0.0 out of 10
N/A
The DataKitchen DataOps Platform aims to automate key functions of data development & production workflows so data teams can collaborate, quickly innovate & deliver error-free, on-demand insight. Tool-Agnostic DataOps Platform supports an array of native tooling integrations & flexible methods for integrating new tools as they come available. Meta-Orchestration Meta-orchestrates all the steps in production & development…N/A
GitLab
Score 8.7 out of 10
N/A
GitLab is an intelligent orchestration platform for DevSecOps, where software teams enable AI at every stage of the software lifecycle to ship faster. The platform enables teams to automate repetitive tasks across planning, building, securing, testing, deploying, and maintaining software.
$0
per month per user
Pricing
DataKitchen DataOps PlatformGitLab
Editions & Modules
No answers on this topic
GitLab Free (self-managed)
$0
GitLab Free
$0
GitLab Premium
$29
per month per user
GitLab Premium (self-managed)
$29
per month per user
GitLab Ultimate
Contact Sales
GitLab Ultimate (self-managed)
Contact Sales
Offerings
Pricing Offerings
DataKitchen DataOps PlatformGitLab
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
YesYes
Entry-level Setup FeeNo setup feeOptional
Additional DetailsGitLab Credits enable flexible, consumption-based access to agentic AI capabilities in the GitLab platform, allowing you to scale AI adoption at your own pace while maintaining cost predictability. Powered by Duo Agent Platform, GitLab’s agentic AI capabilities help software teams to collaborate at AI speed, without compromising quality and enterprise security. If usage exceeds monthly allocations and overage terms are accepted, automated on-demand billing activates without service interruption, so your developers never lose access to AI capabilities they need. Real-time dashboards provide transparency into AI consumption patterns. Software teams can see usage across users, projects, and groups with granular attribution for cost allocation. Automated threshold alerts facilitate proactive planning. Advanced analytics deliver trending, forecasting, and FinOps integration.
More Pricing Information
Community Pulse
DataKitchen DataOps PlatformGitLab
Best Alternatives
DataKitchen DataOps PlatformGitLab
Small Businesses
GitLab
GitLab
Score 8.7 out of 10

No answers on this topic

Medium-sized Companies
GitLab
GitLab
Score 8.7 out of 10
Veracode
Veracode
Score 9.1 out of 10
Enterprises
GitLab
GitLab
Score 8.7 out of 10
Veracode
Veracode
Score 9.1 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
DataKitchen DataOps PlatformGitLab
Likelihood to Recommend
-
(0 ratings)
8.4
(152 ratings)
Likelihood to Renew
-
(0 ratings)
9.0
(5 ratings)
Usability
-
(0 ratings)
10.0
(6 ratings)
Performance
-
(0 ratings)
9.0
(1 ratings)
Support Rating
-
(0 ratings)
10.0
(12 ratings)
Product Scalability
-
(0 ratings)
10.0
(1 ratings)
User Testimonials
DataKitchen DataOps PlatformGitLab
Likelihood to Recommend
DataKitchen
No answers on this topic
GitLab
GitLab is good if you work a lot with code and do complex repository actions. It gives you a very good overview of what were the states of your branches and the files in them at different stages in time. It's also way easier and more efficient to write pipelines for CI\CD. It's easier to read and it's easier to write them. It takes fewer clicks to achieve the same things with GitLab than it does for competitor products.
Read full review
Pros
DataKitchen
No answers on this topic
GitLab
  • GitLab excels in managing code versions, allowing easy tracking of changes, branch management, and merging contributions.
  • It helps maintain code stability and reliability, saving time and effort in the development or research workflow.
  • Powerful code review features, enabling collaboration and feedback among team members.
  • Robust project management features, including issue tracking, kanban boards, and milestones.
Read full review
Cons
DataKitchen
No answers on this topic
GitLab
  • CI variables management is sometimes hard to use, for example, with File type variables. The scope of each variable is also hard to guess.
  • Access Token: there are too many types (Personal, Project, global..), and it is hard to identify the scope and where it comes from once created.
  • Runners: auto-scaled runners are for the moment hard to put in place, and monitoring is not easy.
Read full review
Likelihood to Renew
DataKitchen
No answers on this topic
GitLab
I really feel the platform has matured quite faster than others, and it is always at the top of its game compared to the different vendors like GitHub, Azure pipelines, CircleCI, Travis, Jenkins. Since it provides, agents, CI/CD, repository hosting, Secrets management, user management, and Single Sign on; among other features
Read full review
Usability
DataKitchen
No answers on this topic
GitLab
I find it easy to use, I haven't had to do the integration work, so that's why it is a 9/10, cause I can't speak to how easy that part was or the initial set up, but day to day use is great!
Read full review
Reliability and Availability
DataKitchen
No answers on this topic
GitLab
I've never had experienced outages from GItlab itself, but regarding the code I have deployed to Gitlab, the history helps a lot to trace the cause of the issue or performing a rollback to go back to a working version
Read full review
Performance
DataKitchen
No answers on this topic
GitLab
GItlab reponsiveness is amazing, has never left me IDLE. I've never had issues even with complex projects. I have not experienced any issues when integrating it with agents for example or SSO
Read full review
Support Rating
DataKitchen
No answers on this topic
GitLab
At this point, I do not have much experience with Gitlab support as I have never had to engage them. They have documentation that is helpful, not quite as extensive as other documentation, but helpful nonetheless. They also seem to be relatively responsive on social media platforms (twitter) and really thrived when GitHub was acquired by Microsoft
Read full review
Alternatives Considered
DataKitchen
No answers on this topic
GitLab
Gitlab seems more cutting-edge than GitHub; however, its AI tools are not yet as mature as those of CoPilot. It feels like the next-generation product, so as we selected a tool for our startup, we decided to invest in the disruptor in the space. While there are fewer out-of-the-box templates for Gitlab, we have never discovered a lack of feature parity.
Read full review
Scalability
DataKitchen
No answers on this topic
GitLab
I think is very well designed, and like any VCS it works as intended
Read full review
Return on Investment
DataKitchen
No answers on this topic
GitLab
  • GitLab cut down our spent on container, package and infrastructure registry
  • Best thing is we can now have everything in single platform which cost effective too
  • Quality of support is really good and they do have emergency support team as well which is great
Read full review
ScreenShots

DataKitchen DataOps Platform Screenshots

Screenshot of Meta-Orchestration
Data organizations may be hierarchical and siloed, but analytics production cuts across teams, locations, and environments. The DataKitchen Platform meta-orchestrates all the steps in your production and development pipelines (and even pipelines of pipelines), providing a coherent framework for inter-team collaboration that transcends heterogeneous toolchains and distributed data centers.Screenshot of Environment Creation & Management
With the DataKitchen Platform, create Kitchen workspaces in minutes – not weeks or months – to provide developers with a controlled and secure space to work. Kitchens contain pre-configured tools, datasets, hardware, and tests – everything users need to create and innovate.  When new analytics are ready, Kitchens streamline an individual’s work into a team’s work and eventually into production by seamlessly merging to aligned environments.Screenshot of Continuous Deployment
Analytics can’t be agile with manual, error-prone, and time-consuming release processes. The DataKitchen Platform automates the end-to-end deployment process allowing analytics teams to test and release new analytics on-demand. Kitchens align and integrate toolchain environments so continuous deployment orchestrations can easily migrate analytics to production.Screenshot of Automated Testing & Monitoring
Automated testing and monitoring are foundational to DataOps. The Platform enables you to dramatically improve data quality by catching costly and embarrassing data errors early.  Embed automated tests at every step in your production and development pipelines. Use failures as an opportunity to add more tests and increase the reliability of your pipelines over time. Preset alerts to increase agility and reduce data downtime.Screenshot of Collaboration & Sharing
DataOps is a team effort, and the DataKitchen Platform fosters collaboration by providing a common place to work and a single view of the end-to-end analytic process.  Team members innovate and experiment in separate but aligned Kitchens, then integrate the collective work with confidence.  Teams can easily save and share commonly used parts of pipelines as Ingredients – a significant productivity multiplier.Screenshot of DataOps Process Analytics
You can’t improve what you don’t measure. The DataKitchen Platform provides unprecedented visibility into the state of your data operations.  Process metrics show how your teams are increasing collaboration, improving productivity, expanding test coverage, reducing errors, speeding deployment cycle times, and consistently meeting deadlines.

GitLab Screenshots

Screenshot of What is Intelligent Orchestration for DevSecOps?Screenshot of an overview of GitLab Duo Agent PlatformScreenshot of a new agent creation screen