Here’s the difference between Apache Spark and dbt. The comparison is based on pricing, deployment, business model, and other important factors.
Apache Spark is an open-source unified analytics engine for large-scale data processing. Spark provides an interface for programming entire clusters with implicit data parallelism and fault tolerance.
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.
Overview | ||
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Categories | Data Modelling and Transformation | Data Modelling and Transformation |
Stage | Late Stage | Early Stage |
Target Segment | Mid Size, Enterprise | Enterprise, Mid size |
Deployment | On Prem | SaaS |
Business Model | Open Source | Open Source |
Pricing | Freemium | Free trial, Contact Sales |
Location | US | US |
Companies using it | ||
Contact info |