Here’s the difference between dbt and Google BigQuery. 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.
BigQuery is a fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. It is a Platform as a Service that supports querying using ANSI SQL. It also has built-in machine learning capabilities. BigQuery was announced in May 2010 and made generally available in November 2011.
Overview | ||
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Categories | Data Modelling and Transformation | Data Warehouses |
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 | Contact Sales |
Location | US | US |
Companies using it | ||
Contact info |