Here’s the difference between dbt and Snowflake. 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.
Snowflake delivers the Data Cloud — a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance. Inside the Data Cloud, organizations unite their siloed data, easily discover and securely share governed data, and execute diverse analytic workloads. Wherever data or users live, Snowflake delivers a single and seamless experience across multiple public clouds. Snowflake’s platform is the engine that powers and provides access to the Data Cloud, creating a solution for data warehousing, data lakes, data engineering, data science, data application development, and data sharing.
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 | California, US |
Companies using it | ||
Contact info |