Apache Airflow vs Azkaban

Struggling to choose between Apache Airflow and Azkaban? Both products offer unique advantages, making it a tough decision.

Apache Airflow is a Ai Tools & Services solution with tags like scheduling, pipelines, workflows, data-pipelines, etl.

It boasts features such as Directed Acyclic Graphs (DAGs) - modeling workflows as code, Dynamic task scheduling, Extensible plugins, Integration with databases, S3, and other environments, Monitoring, alerting, and logging, Scalable - handles data pipelines across organizations, Web server & UI to visualize pipelines and pros including Open source and free, Active community support, Modular and customizable, Robust scheduling capabilities, Integration with many services and databases, Scales to large workflows.

On the other hand, Azkaban is a Ai Tools & Services product tagged with workflow, scheduler, hadoop, jobs, open-source.

Its standout features include Web-based workflow scheduler, Allows creating, managing and monitoring workflows, Built-in authentication and authorization, Supports workflow dependencies, Provides execution logs and metrics, Plugin system for extensibility, Alerting and failure handling, and it shines with pros like Open source and free, Easy to use interface, Scalable and reliable, Integrates well with Hadoop, Good documentation and community support.

Feature	Apache Airflow	Azkaban
Overall Score	N/A	N/A
Primary Category	Ai Tools & Services	Ai Tools & Services

Product Overview

Apache Airflow

Description: Apache Airflow is an open-source workflow management platform used to programmatically author, schedule and monitor workflows. It provides a graphical interface to visualize pipelines and integrates with databases and other environments.

Azkaban

Description: Azkaban is an open source workflow scheduler created at LinkedIn to run Hadoop jobs. It allows users to easily create, schedule and monitor workflows made up of different jobs. Azkaban provides a web interface and scheduling capabilities to manage dependencies between jobs.

Key Features Comparison

Apache Airflow Features

• Directed Acyclic Graphs (DAGs) - modeling workflows as code
• Dynamic task scheduling
• Extensible plugins
• Integration with databases, S3, and other environments
• Monitoring, alerting, and logging
• Scalable - handles data pipelines across organizations
• Web server & UI to visualize pipelines

Azkaban Features

• Web-based workflow scheduler
• Allows creating, managing and monitoring workflows
• Built-in authentication and authorization
• Supports workflow dependencies
• Provides execution logs and metrics
• Plugin system for extensibility
• Alerting and failure handling

Pros & Cons Analysis

Apache Airflow

Pros

• Open source and free
• Active community support
• Modular and customizable
• Robust scheduling capabilities
• Integration with many services and databases
• Scales to large workflows

Cons

• Steep learning curve
• Can be complex to set up and manage
• Upgrades can break DAGs
• No native support for real-time streaming
• UI and API need improvement

Azkaban

Pros

• Open source and free
• Easy to use interface
• Scalable and reliable
• Integrates well with Hadoop
• Good documentation and community support

Cons

• Limited visualization and monitoring
• Steep learning curve for advanced features
• Not ideal for real-time workflows
• No commercial support offered

Pricing Comparison

Apache Airflow

• Open Source

Azkaban

• Open Source