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Azure Pipelines vs. DataKitchen DataOps Platform

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Azure Pipelines

18 Reviews and Ratings

DataKitchen DataOps Platform

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Azure Pipelines

    Score8.5 out of 10
    		N/AUsers can automate builds and deployments with Azure Pipelines. Build, test, and deploy Node.js, Python, Java, PHP, Ruby, C/C++, .NET, Android, and iOS apps. Run in parallel on Linux, macOS, and Windows. Azure Pipelines can be purchased standalone, but it is also part of Azure DevOps Services agile development planning and CI/CD suite.N/A

    DataKitchen DataOps Platform

    		N/AN/AThe 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
    Pricing
    Azure PipelinesDataKitchen DataOps Platform
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    Azure PipelinesDataKitchen DataOps Platform
    Free Trial
    NoNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
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    User Ratings
    Azure PipelinesDataKitchen DataOps Platform
    Likelihood to Recommend
    7.0
    (3 ratings)
    -
    (0 ratings)
    User Testimonials
    Azure PipelinesDataKitchen DataOps Platform
    Likelihood to Recommend
    Microsoft
    It is good tool if you are doing continuous improvements in your code and you wish it goes live whenever you push code to GitHub. So integrating Azure Pipeline, it automatically does CI/CD in the background once you push code/merge code and it is live in few minutes. It also does some automated tests if you have wrote scripts
    Incentivized
    Verified User
    Read full review
    DataKitchen
    No answers on this topic
    Pros
    Microsoft
    • Integration with SonarQube
    • Integration with Azure DevOps
    • Integration with GitHub
    Incentivized
    Matthew Budram
    Software Architect
    Read full review
    DataKitchen
    No answers on this topic
    Cons
    Microsoft
    • The errors which we got sometimes are not clearly enough.
    • There are some let's say hidden options, they could be more visible
    • When the process is running we have to remember about manually refreshing to see the current status because it doesn't work automatically
    Incentivized
    Verified User
    Read full review
    DataKitchen
    No answers on this topic
    Alternatives Considered
    Microsoft
    We have used the GitHub CI/CD. Earlier we were using the Azure Pipelines but after GitHub had their actions, we integrated that for CI/CD. It runs the tests and makes a production build which can be live. GitHub CI/CD is more useful because we have to make script only once then just by few changes we can deploy it onto Azure, AWS, Google anywhere so we found it more convenient
    Incentivized
    Verified User
    Read full review
    DataKitchen
    No answers on this topic
    Return on Investment
    Microsoft
    • we have had outages from Azure in the past
    Incentivized
    Matthew Budram
    Software Architect
    Read full review
    DataKitchen
    No answers on this topic
    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.