Apache Airflow vs. Astro by Astronomer

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Airflow
Score 8.4 out of 10
N/A
Apache Airflow is an open source tool that can be used to programmatically author, schedule and monitor data pipelines using Python and SQL. Created at Airbnb as an open-source project in 2014, Airflow was brought into the Apache Software Foundation’s Incubator Program 2016 and announced as Top-Level Apache Project in 2019. It is used as a data orchestration solution, with over 140 integrations and community support.N/A
Astro by Astronomer
Score 10.0 out of 10
N/A
For data teams looking to increase the availability of trusted data, Astronomer provides Astro, a data orchestration platform, powered by Airflow. Astro enables data engineers, data scientists, and data analysts to build, run, and observe pipelines-as-code. Astronomer is the driving force behind Apache Airflow™, the de facto standard for expressing data flows as code. Airflow is downloaded more than 8 million times each month and is used by hundreds of thousands of teams around the world.N/A
Pricing
Apache AirflowAstro by Astronomer
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache AirflowAstro by Astronomer
Free Trial
NoYes
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeOptional
Additional Details
More Pricing Information
Community Pulse
Apache AirflowAstro by Astronomer
Top Pros

No answers on this topic

Top Cons

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Features
Apache AirflowAstro by Astronomer
Workload Automation
Comparison of Workload Automation features of Product A and Product B
Apache Airflow
8.2
9 Ratings
0% below category average
Astro by Astronomer
-
Ratings
Multi-platform scheduling8.89 Ratings00 Ratings
Central monitoring8.49 Ratings00 Ratings
Logging8.19 Ratings00 Ratings
Alerts and notifications7.99 Ratings00 Ratings
Analysis and visualization7.99 Ratings00 Ratings
Application integration8.49 Ratings00 Ratings
Best Alternatives
Apache AirflowAstro by Astronomer
Small Businesses

No answers on this topic

Skyvia
Skyvia
Score 9.8 out of 10
Medium-sized Companies
ActiveBatch Workload Automation
ActiveBatch Workload Automation
Score 8.3 out of 10
Astera Data Pipeline Builder (Centerprise)
Astera Data Pipeline Builder (Centerprise)
Score 8.9 out of 10
Enterprises
Redwood RunMyJobs
Redwood RunMyJobs
Score 9.3 out of 10
Control-M
Control-M
Score 9.2 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache AirflowAstro by Astronomer
Likelihood to Recommend
7.3
(9 ratings)
10.0
(1 ratings)
User Testimonials
Apache AirflowAstro by Astronomer
Likelihood to Recommend
Apache
For a quick job scanning of status and deep-diving into job issues, details, and flows, AirFlow does a good job. No fuss, no muss. The low learning curve as the UI is very straightforward, and navigating it will be familiar after spending some time using it. Our requirements are pretty simple. Job scheduler, workflows, and monitoring. The jobs we run are >100, but still is a lot to review and troubleshoot when jobs don't run. So when managing large jobs, AirFlow dated UI can be a bit of a drawback.
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Astronomer, Inc.
Astronomer is well suited for workflow and dependency management for enterprise-level data lakes. It is not a product for data processing though. Different source systems can be integrated, it also provides powerful interfaces for alerting and monitoring. Easy to build DAGs, graphical UI, API support makes the product more user-friendly as well. Astronomer also does a great job on user training.
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Pros
Apache
  • In charge of the ETL processes.
  • As there is no incoming or outgoing data, we may handle the scheduling of tasks as code and avoid the requirement for monitoring.
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Astronomer, Inc.
  • Workflow management
  • Wide availability of plugins
  • Dependency management on upstream
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Cons
Apache
  • they should bring in some time based scheduling too not only event based
  • they do not store the metadata due to which we are not able to analyze the workflows
  • they only support python as of now for scripted pipeline writing
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Astronomer, Inc.
  • More language agnostic
  • Flexible fork and join capabilities
  • Near real time UI updates in case of deployment of enhanced DAGs
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Alternatives Considered
Apache
There are a number of reasons to choose Apache Airflow over other similar platforms- Integrations—ready-to-use operators allow you to integrate Airflow with cloud platforms (Google, AWS, Azure, etc) Apache Airflow helps with backups and other DevOps tasks, such as submitting a Spark job and storing the resulting data on a Hadoop cluster It has machine learning model training, such as triggering a Sage maker job.
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Astronomer, Inc.
Astronomer is a fast, secure, scalable workload management solution. It provides world-class user training along with easy to interact support.
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Return on Investment
Apache
  • A lot of helpful features out-of-the-box, such as the DAG visualizations and task trees
  • Allowed us to implement complex data pipelines easily and at a relatively low cost
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Astronomer, Inc.
  • It helps to build scalable, available and low maintenance workloads
  • Integrated Alerts and notifications helps to detect load issues in the early stages
  • Ensures meeting data SLAs
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