Apache Maven vs. DataKitchen DataOps Platform

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Maven
Score 9.2 out of 10
N/A
Apache Maven is an open source build automation tool.N/A
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
Pricing
Apache MavenDataKitchen DataOps Platform
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache MavenDataKitchen 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
Community Pulse
Apache MavenDataKitchen DataOps Platform
Best Alternatives
Apache MavenDataKitchen DataOps Platform
Small Businesses
GitLab
GitLab
Score 8.7 out of 10
GitLab
GitLab
Score 8.7 out of 10
Medium-sized Companies
GitLab
GitLab
Score 8.7 out of 10
GitLab
GitLab
Score 8.7 out of 10
Enterprises
GitLab
GitLab
Score 8.7 out of 10
GitLab
GitLab
Score 8.7 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache MavenDataKitchen DataOps Platform
Likelihood to Recommend
9.0
(14 ratings)
-
(0 ratings)
Usability
8.0
(1 ratings)
-
(0 ratings)
Support Rating
5.1
(3 ratings)
-
(0 ratings)
User Testimonials
Apache MavenDataKitchen DataOps Platform
Likelihood to Recommend
Apache
Maven is great if you have an application with a lot of third-party dependencies and don’t want each developer to keep track of where the dependency can be downloaded. It’s also a great way to make it easy for a new developer to be able to build the application. It’s less suitable for simple projects without any third-party dependencies.
Read full review
DataKitchen
No answers on this topic
Pros
Apache
  • If you are building in the Java ecosystem, then Maven definitely has the biggest repository of artifacts needed for such projects.
  • It has a very simple to use extendable architecture. Everything is configurable through the Pom.xml file which is very simple to follow.
Read full review
DataKitchen
No answers on this topic
Cons
Apache
  • Maven provides a very rigid model that makes customization tedious and sometimes impossible. While this can make it easier to understand any given Maven build, as long as you don’t have any special requirements, it also makes it unsuitable for many automation problems.
  • Maven has few, built-in dependency scopes, which forces awkward module architectures in common scenarios like using test fixtures or code generation. There is no separation between unit and integration tests
Read full review
DataKitchen
No answers on this topic
Usability
Apache
The overall usability of Apache Maven is very good to us. We were able to incorporate it into our company's build process pretty quickly. We deployed it to multiple teams throughout the entire enterprise. We got good feedback from our developers stating that Apache Maven has simplified their build process. It also allowed to to standardize the build process for the entire enterprise, thus ensure that each development team is using the same, consistent process to build code.
Read full review
DataKitchen
No answers on this topic
Support Rating
Apache
I can't speak to the support, as I've never had issues. Apache Maven "just works," and errors were user errors or local nexus errors. Apache Maven is a great build/dependency management tool. I give it a 9/10 because occasionally the error message don't immediately indicate a solution...but again, those errors were always user or configuration errors, and the Maven documentation is extensive, so I don't find fault in Maven, but in its users.
Read full review
DataKitchen
No answers on this topic
Alternatives Considered
Apache
Ant, Maven's opposing framework, is often a point of comparison. Although Ant does not require formal conventions, it is procedural in the sense that you must tell Ant exactly what to do and when. It also lacks a lifecycle, along with goal definition and dependencies. Maven, on the other hand, requires less work as it knows exactly where your source code is as long as the pom.xml file is generated.
Read full review
DataKitchen
No answers on this topic
Return on Investment
Apache
  • It was very handy to roll out organization level frameworks to be used by diverse departments and business
  • Consistent build artifacts enabling smooth release cycles, thereby enabling to adhere to release calendars and feature rollouts
  • Reduced 80 man hours of work every release cycle
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.