Here’s the difference between dbt and Google Cloud Dataflow. The comparison is based on pricing, deployment, business model, and other important factors.
Dbt is an analytics engineering workflow tool. The command line based build tool enables data analysts and engineers to transform data in their warehouse and can take ownership of the entire analytics engineering workflow, from writing data transformation code to deployment and documentation. It automates data quality testing, deploys analytics code, and delivers data with documentation.
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.
Overview | ||
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Categories | Data Modelling and Transformation | Data Streaming |
Stage | Early Stage | Late Stage |
Target Segment | Enterprise, Mid size | Enterprise, Mid size |
Deployment | SaaS | SaaS |
Business Model | Open Source | Commercial |
Pricing | Free trial, Contact Sales | Freemium |
Location | US | US |
Companies using it | ||
Contact info |