Compare - Airflow VS Google Cloud Dataflow

Here’s the difference between Airflow and Google Cloud Dataflow. The comparison is based on pricing, deployment, business model, and other important factors.

About Airflow

Apache Airflow is a workflow automation and scheduling system that can be used to author and manage data pipelines. Airflow uses workflows made of directed acyclic graphs (DAGs) of tasks.

About Google Cloud Dataflow

Google Cloud Dataflow is a cloud-based data processing service for both batch and real-time data streaming applications. It enables developers to set up processing pipelines for integrating, preparing and analyzing large data sets, such as those found in Web analytics or big data analytics applications. The Cloud Dataflow software expands on earlier Google parallel processing projects, including MapReduce, which originated at the company. Cloud Dataflow is designed to bring to entire analytics pipelines the style of fast parallel execution that MapReduce brought to a single type of computational sort for batch processing jobs.

Comparison Table

Overview
CategoriesWorkflow OrchestrationData Streaming
StageEarly StageLate Stage
Target SegmentEnterprise, Mid sizeEnterprise, Mid size
DeploymentSaaSSaaS
Business ModelOpen SourceCommercial
PricingNot AvailableFreemium
LocationUSUS
Companies using it
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Paypal logoBlaBlaCar logo
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