Here’s the difference between Databricks and dbt. The comparison is based on pricing, deployment, business model, and other important factors.
Databricks provides a data lakehouse that unifies your data warehousing and AI use cases on a single platform. With Databricks, you can implement a common approach to data governance across all data types and assets, and execute all of your workloads across data engineering, data warehousing, data streaming, data science, and machine learning on a single copy of the data. Built on open source and open standards, with hundreds of active partnerships, Databricks easily integrates with your modern data stack. Additionally, Databricks uses an open standards approach to data sharing to eliminate ecosystem restrictions. Finally, Databricks provides a consistent data platform across clouds to reduce the friction of multicloud environments. Today, Databricks has over 7000 customers, including Amgen, Walmart, Disney, HSBC, Shell, Grab, and Instacart.
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.
|Categories||Data Warehouses, Data Lakes||Data Modelling and Transformation|
|Stage||Late Stage||Early Stage|
|Target Segment||Enterprise, Mid size||Enterprise, Mid size|
|Business Model||Commercial||Open Source|
|Pricing||Freemium, Contact Sales||Free trial, Contact Sales|
|Location||San Francisco, US||US|
|Companies using it|