Astronomer Reviews, Ratings & Features 2026 | Gartner Peer Insights

Gartner defines DataOps as the collaborative data management practice focusing on improving communication, continuous integration, automation, observability and operations of data flows between data managers, data consumers, and their teams across the organization. DataOps tools connect and orchestrate data pipelines across heterogeneous systems. Data and analytics leaders are the buyers in this emerging market. The primary audience for DataOps tools is “data manager” personas like, data engineers, data integration developers, operations/incident analysts, database administrators and data architects. The secondary audience is “data consumer” personas like business analysts, business intelligence developers, data scientists and citizen roles (departmental users who are domain experts, but less technical).

Active

Find the top DataOps Tools with Gartner. Compare and filter by verified product reviews and choose the software that’s right for your organization.

DataOps Tools

Astro

Astronomer

Data And Analytics Manager

An easy-to-use managed instance of Airflow that removes a lot of the frustrations surrounding setup and infrastructure. 

50M - 250M USD

250M - 500M USD

1B - 3B USD

<50M USD

3B - 10B USD

500M - 1B USD

30B + USD

10B - 30B USD

Gov't/PS/ED <5,000 Employees

Data Analyst

It's very efficient in performance, scaling and setup is easier.

Security Analyst

We use Astro for workflow standarization and process visibility across the board. Overall, the experience has been positive; it reduced manual effort and made it easier to automate repetitive tasks. Previously, we were using self-hosted Apache Airflow, wich consumed not only financial resources (AWS infraestructure) but also significant operational time from our infraestructure team, wich we are now saving.
We encontred some initial issues during implementation, mainly related to the initial dabase config with AWS. However, after resolving those issues, we did not experience futher problems.

Databricks

Other...

Ascend.io

Stonebranch

DataOps.live

HighByte

Astronomer is the company behind Astro, a unified DataOps platform powered by Apache Airflow. Astro enables data teams to build, run, observe, and manage mission-critical data pipelines for data-, analytics-, and AI-driven applications. It supports the development of reliable data products by enabling workflow orchestration, observability, and automation. With built-in data observability features such as logging, metrics, and lineage tracking, Astronomer helps teams monitor and troubleshoot workflows in production. Organizations across industries use Astronomer to operationalize data across cloud, hybrid, and on-premises environments.


Astronomer empowers data teams to bring mission-critical analytics, AI, and software to life and is the company behind Astro, the industry-leading DataOps platform powered by Apache Airflow®. Astro accelerates building reliable data products that unlock insights, unleash AI value, and powers data-driven applications. Trusted by more than 700 of the world’s leading enterprises, Astronomer lets businesses do more with their data. To learn more, visit www.astronomer.io Apache® and Apache Airflow® are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries. No endorsement by the Apache Software Foundation is implied by the use of these marks. All other trademarks are the property of their respective owners.

Astronomer is a company committed to enabling data teams to realize the full potential of critical analytics, AI, and software applications. They have created the Astro, a DataOps platform built on the powerhouse of Apache Airflow®. Astro is designed to facilitate the construction of reliable data products that can provide crucial insights, tap into the capabilities of artificial intelligence, and power data-oriented applications. Astronomer is highly regarded by leading global enterprises and assists businesses in fully utilizing their data reserves.

Reviews

Ratings Overview

Overall experience with

Favorable Review

Reduced Operational Overhead With Astro, Yet Advanced Documentation Needs Improvement

Critical Review

Faster Start Times and Pipeline Building Highlighted Amid Customization Constraints

Likes and dislikes about

likes

dislikes