Gartner Market Guide to DataOps Software

Gartner released its 'Market Guide to DataOps Tools' The document they wrote is exceptionally close to what DataKitchen sees in the market and what our products do! Here is our take on the guide.

We are excited that Gartner released its ‘Market Guide to DataOps Tools’! The document they wrote is exceptionally close to what we see in the market and what our products do! This document is essential because buyers look to Gartner for advice on what to do and how to buy IT software. The two things we are most excited about are:

First, DataOps is distinct from all Data Analytic tools. As founders, we sat in a room eight years ago (when all the rage was Hadoop, data prep, and data lakes) and debated — will there ever be an ‘ops’ layer that sits next to all the current data tools? We can see in the diagram below that Gartner sees DataOps tools as distinct from the various Database/ETL/viz/AI/governance tools that make up the typical data stack today.


gartner dataops

Second, the components of a DataOps software solution match very well with how we have thought about the market and the features of our products. When we sat in that room seven years ago, we had another debate: Will the types of agile DevOps tools that make software teams successful apply to data teams? What is missing? If so, what are the key components? How is DevOps different than DataOps? What software should we build?


   Here is what Gartner says are the key components of DataOps software (grouping by DataKitchen):


  • DataOps Automationcapabilities such as connectivity to your data stack … workflow & release automation.”
    • Orchestration: Connectivity, workflow automation, lineage, scheduling, logging, troubleshooting, and alerting
    • Environment Management: Infrastructure as code, resource provisioning, environment repository templates, credentials management
    • Deployment Automation: Version control, release pipelines, approvals, rollback, and recovery
    • Test Automation: Business rules validation, test scripts management, test data management
  • DataOps Observability “Prioritize tools that give a ‘single pane of glass.”
    • Observability: Monitoring live/historic workflows, insights into workflow performance, and cost metrics impact analysis

As a vendor, we work to influence industry analysts like Gartner, who also help guide us. Industry analysts, in turn, both listen to and influence buyers. Gartner is very customer driven; they wrote this report because they have seen 40% annual gains in DataOps analyst inquiries. Given our founding team’s background in software and running data teams, it was not a great leap to see that this was a huge problem waiting to be solved. Now there are dozens of vendors in the greater DataOps category, which is an excellent result for everyone in the industry. And this document is one of many that Gartner, Forrester, Eckerson, and other analysts have written on DataOps automation, testing, and observability.

We see teams do amazing things with our DataOps software. We tell all our prospects if you strive for zero errors and can deploy quickly with low risk, your team will see incredible gains in the amount of work they create. Gartner agrees: 

“By 2025, a … team guided by DataOps practices and tools will be 10 times more productive than teams that do not use DataOps.”

The next step is for Gartner to publish a ‘magic quadrant’ … which, for DataKitchen, is the final step to bringing a new DataOps software category to life. It may be some time before that happens. Still, our job at DataKitchen is to make our customers successful so that in 2025, we can write another self-congratulatory blog post touting our position as the Magic Quadrant ‘leader’ in DataOps software!

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