Airflow Reviews & Pricing

by Apache Software Foundation | Founded 2014, San Francisco, CA

REQUEST WITH NO OBLIGATION$ Request Pricing Get Free Demo

Request Pricing Request Demo

Overview Benefits Reviews Features

Categories:

What is Airflow?

Industry Specialties: Serves all industries

Airflow is an open-source Python framework that allows authoring, scheduling and monitoring of complex data sourcing tasks for big data pipelines. Aligned with the DevOps mantra of “Configuration as Code,” it allows developers to orchestrate workflows and programmatically handle execution dependencies such as job retries and alerting. Through the use of Directed Acyclic Graphs (DAGs), developers can customize pipeline processes as needed by using multi-step workflows. They can run part of the workflow at any time, even when tasks are being updated in real time.

Besides out-of-the-box integrations with MySQL, Microsoft Server and SaaS platforms, it also provides custom connections to plugins. Robust and flexible, it is free to download for all users.

PRICE

COMPANY SIZE

DEPLOYMENT

PLATFORM

Try Before You Buy.

Request a Free Demo Today!

Request Demo

It's completely free!

User Sentiment

Based on 31 reviews:

Add your rating:

Product Screenshots and Videos

Airflow Benefits and Insights

Why use Airflow?

Key differentiators & advantages of Airflow

Dependency Management: Define tasks through basic units of abstraction known as custom operators. Set up workflows using sets of extensible operators through DAGs. Create custom, reusable workflows by extending existing operators through its entry point for external plugins. Manage task dependencies efficiently while handling job fails and task retries.
Integrations: Integrate seamlessly with Apache Spark, Hive, BigQuery and EMR and cloud-based software through built-in operators.Connect to MySQL and Microsoft SQL Server databases, as well as SaaS platforms such as Salesforce, Facebook and Stripe through its out-of-the-box plugins.
User-Friendly Interface: Its intuitive interface helps monitor scheduling and running of data pipelines with graphs, tree views, code views and Gantt charts. Click on a task instance to view a rich, actionable context menu.
Scalability: Scales with the organization as it grows by running multiple tasks in parallel. Its modular architecture enables handling of large task loads through an efficient message queue for Airflow workers.
Failure Handling: Debug job and scheduling issues by monitoring them through custom visualizations, such as charts. View historical data of jobs and improve them by adding retry policies and alerts in case of failures or timeouts

Industry Expertise

Airflow provides workflow authoring and management services to enterprises across the world. These include service aggregators, retail, software, investment banking, social media, sports, snacks and beverages vendors and many more.

Airflow Reviews

Average customer reviews & user sentiment summary for Airflow:

31 reviews

86%

of users would recommend this product

Key Features

Directed Acyclic Graphs (DAGs): Create and schedule batch-jobs efficiently through DAGs. Run ETL workloads faster with concurrent tasks, and run concurrent DAGs at the same time.
Task Scheduling: Run workflows through manual action or external triggers, or schedule them to run at specific times. Change the workflow logic at any point, and run the complete logic, or just part of it. Trigger backfills from the UI — execute the new logic on previously completed workflows.
Executor: Executes tasks through the Airflow workers and follows specified dependencies. Handles resource utilization and allocates tasks as per worker availability for optimal performance.
Python Code: Control workflows through instantiation of Python code-based data pipeline. Leverage custom operators and hooks in addition to pre-defined ones.
Batch Processing: Runs tasks in batches at certain intervals or triggers to manage large, repetitive tasks. Assign specific times for the batch runs to optimize system functionality.

Limitations

Some of the product limitations include:

It has limited support for Microsoft Azure
Relies on the system time zone (instead of UTC) for scheduling, requiring the entire system to be run in the same time zone
The Scheduler works separately for scheduled jobs and backfill jobs; this might result in different values for variables dependent on both types of jobs

Suite Support

Access the online community on the vendor’s website for possible resolution to issues. Read documentation, tutorials and blogs, join meetups or go through its use cases for answers to queries. Or, ask an ad-hoc question on Slack, accessible through signing up on the vendor’s website.

Email: Not available. Instead, subscribe to the [email protected] or [email protected] mailing lists to keep up with discussions.

Phone: Not available.

Training: The vendor doesn’t offer any training programs. However, many third-party websites provide paid training courses.

Tickets: Create an account on Github and sign-in to submit a support request.