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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Mattermost logo
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DataRobot logo
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Medically Home logo
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X-team logo
Collibra logo
Dotz Inc. logo
Affirm logo
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Convoy logo
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Too Good To Go logoAzimo logo
Insight Partner logo
Bol logo
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Envoy logo
Stride logo
Beamery logo
EZ Texting logo
Ruby Labs logo
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Photobox logo
Knotch logo
Pluralsight logo
Wallbox logo
Twilio logo
ManyPets logo
Lotum logo
OneFootball logo
Clark logo
Databand.com logo
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Getindata logo
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terality logoswile logo
catch.com.au logo
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Hubla logo
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InfoPrice logoCraft logo
Bukuwarung logo
Fanatics Inc logo
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JMAN Group logoCortex logo
Mage logo
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thinking machines data science logo
L'Oréal logo
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Spotify logo
Dotz Inc. logo
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