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Apache Airflow

Apache Airflow

Overview

What is Apache Airflow?

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…

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Learn from top reviewers

Scalable Scheduling Framework and Orchestration tool

Rating: 10 out of 10
January 7, 2025
IncentivizedVetted ReviewVerified User
We are using Apache Airflow as an orchestration tool in data engineering workflows in gaming product. We are scheduling multiple jobs i.e hourly / daily / weekly / monthly. ...
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Anshuman Varshney
Engineer - Engineering
Engineering Manager
Gameskraft
Apache Airflow6 years of experience

Apache Airflow for Startups

Rating: 8 out of 10
December 18, 2024
IncentivizedVetted ReviewVerified User
Used Airflow for Analytics & Reporting
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Alok Pabalkar
Team Lead - Research & Development
Co-Founder & CTO
Mini Venture Lab Private Limited
Apache Airflow1 year of experience

Apache AirFlow - Love the Features, Love the Reliability.. Love if the UI get modenized!

Rating: 7 out of 10
June 26, 2022
IncentivizedVetted ReviewVerified User
We use apache airflow as part of our DAG scheduler and health monitoring tool. It serves as a core component in ensuring our scheduled jobs are run, the ability to allow us to...
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Victor Tay
Engineer - Product Management
Engineer
IronNet CyberSecurity
Apache Airflow1 year of experience

A great solution to help orchestrate workflows and pipelines

Rating: 9 out of 10
June 22, 2022
IncentivizedVetted ReviewVerified User
Apache airflow is a great way to orchestrate workflows and build enterprise data pipelines. It is very easy to configure and setup and would be my go to solution for orchestra...
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Nick Waters
Consultant - Sales
Solutions Engineer
Datameer
Apache Airflow1 year of experience

A very nice job scheduler of DAGs that could become even better

Rating: 7 out of 10
June 13, 2022
IncentivizedVetted ReviewVerified User
We use apache Airflow in GCP as part of Cloud Composer to run all our ETL jobs.
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Nic Georgakopoulos
Manager - Engineering
DevOps
Deloitte Digital
Apache Airflow3 years of experience
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Pricing

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Apache Airflow

Apache Airflow

N/A
Unavailable

What is Apache Airflow?

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…

Entry-level set up fee?

  • No setup fee

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services

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Product Demos

Getting Started with Apache Airflow

YouTube

Apache Airflow | Build your custom operator for twitter API

YouTube
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Features

Workload Automation

Workload automation tools manage event-based scheduling and resource management across a wide variety of applications, databases and architectures

9.8
Avg 8.3
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Product Details

What is Apache Airflow?

Apache Airflow Video

What's coming in Airflow 2.0?

Apache Airflow Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo

Frequently Asked Questions

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.

Reviewers rate Multi-platform scheduling highest, with a score of 10.

The most common users of Apache Airflow are from Enterprises (1,001+ employees).
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Comparisons

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Reviews From Top Reviewers

View all reviews
(1-5 of 7)

Apache Airflow for Automation and scheduling

Rating: 9 out of 10
Incentivized
May 05, 2022
Verified User
Program Manager in Manufacturing
Automotive Company, 5001-10,000 employees
Vetted Review
Verified User
Apache Airflow
3 years of experience
Use Cases and Deployment Scope
We are using Apache Airflow for streamline the data pipelines, creating the workflow, Schedule the workflow as per the need, and also monitor the same, we are solving the problem of fetching the data from hive and then created the complete workflow and also we are using for automation as well.
Pros
  • Smart Automation
  • Highly Scalable
  • Complex Workflow
  • Easy Integration with other system
Cons
  • Documentation part
  • GUI can be improved
  • Reliability issues
Likelihood to Recommend
Apache Airflow is best suited for the data engineers for creating the data workflows, and it is best suitable for the scheduling the workflow and also we can run the python codes as well using apache airflow, and it is suited for the situation where we need scalable solution. Monitoring can be done easily.

A great solution to help orchestrate workflows and pipelines

Rating: 9 out of 10
Incentivized
June 22, 2022
NW
Nick Waters
Solutions Engineer
Datameer (Information Technology & Services, 10,001+ employees)
Vetted Review
Verified User
Apache Airflow
1 year of experience
View profile
Use Cases and Deployment Scope
Apache airflow is a great way to orchestrate workflows and build enterprise data pipelines. It is very easy to configure and setup and would be my go to solution for orchestrating data flows. We use Airflow to integrate our solution via APIs and allow third party solutions to access our solution and data held within in it.
Pros
  • Orchestrate workflows
  • Visualise workflows easily using DAG
  • Integrate 3rd party data sources
Cons
  • Visualisation UI could be improved in my opinion.
  • Enterprise features
  • Performance improvements in bigger deployments.
Likelihood to Recommend
Well suited for anyone that wants to orchestrate data pipelines and workflows. Good for developing, scheduling, and monitoring data workflows and is capable of managing complex enterprise workloads and pipelines. The visual aspect of understanding how your workflows are inter-connected is especially useful.

Scalable Scheduling Framework and Orchestration tool

Rating: 10 out of 10
Incentivized
January 07, 2025
AV
Anshuman Varshney
Engineering Manager
Gameskraft (Information Technology & Services, 501-1000 employees)
Vetted Review
Verified User
Apache Airflow
6 years of experience
Use Cases and Deployment Scope
We are using Apache Airflow as an orchestration tool in data engineering workflows in gaming product.
We are scheduling multiple jobs i.e hourly / daily / weekly / monthly.
We have a lot of requirement for dependent jobs i.e job1 should mandatory run before job2, and Apache Airflow does this work very swiftly, we are utilising multiple Apache Airflow integration with webhook and APIs. Additionally, we are doing a lot of jobs monitoring and SLA misses via Apache Airflow features
Pros
  • Job scheduling
  • Dependent job workflows
  • Failure handling and rerun of workflows
Cons
  • Better User Interface
Likelihood to Recommend
Dependent Job scheduling
Rerun mechanism of workflows
High availability deployment strategies

Apache Airflow software

Rating: 9 out of 10
Incentivized
June 21, 2022
Verified User
Engineer in Engineering
Computer Software Company, 10,001+ employees
Vetted Review
Verified User
Apache Airflow
1 year of experience
Use Cases and Deployment Scope
Apache Airflow is used for the scheduling and orchestration of data pipelines or workflows. Orchestration of data pipelines refers to the sequencing, coordination, scheduling, and managing of complex data pipelines from diverse sources. It is also helpful when your data pipelines change slowly (days or weeks – not hours or minutes), are related to a specific time interval, or are pre-scheduled.
Pros
  • Scheduling of data pipelines or workflows.
  • Orchestration of data pipelines or workflows.
Cons
  • Not intuitive for new users.
  • Setting up Airflow architecture for production is NOT easy.
Likelihood to Recommend
Ease of use—you only need a little python knowledge to get started. Open-source community—Airflow is free and has a large community of active users. Apache Airflow is used for the scheduling and orchestration of data pipelines or workflows. Orchestration of data pipelines refers to the sequencing, coordination, scheduling, and managing of complex data pipelines from diverse sources.

Apache Airflow is flawless

Rating: 9 out of 10
Incentivized
June 24, 2022
Verified User
Engineer in Information Technology
Financial Services Company, 5001-10,000 employees
Vetted Review
Verified User
Apache Airflow
2 years of experience
Use Cases and Deployment Scope
We use Apache Airflow to perform data integration in AWS S3 region. With this we are able to connect to a relational database, easily execute data extracts, and compile them all in multiple flat file segments. Airflow brings a lot of standardization as well as modularity. We also use it to send data to partners and score ML models. It allows us to implement complex data pipelines easily.
Pros
  • Multiple helpful features
  • Very intuitive flow charts
  • Reruns and backfills are very easy
  • SLA and DAGs are easy to set up
Cons
  • Potentially a steep learning curve
  • The browser UI could do with a few enhancements
Likelihood to Recommend
Using Apache Airflow has been extremely helpful, as it means we can get to our endgame faster. This product has enabled us to translate our ideas into projects at a much faster speed than before we had this software. We manage data ingestion and modeling for multiple products and customers within each product. Each has its own pipeline with its own code.
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