dbt-core is a command-line framework for transforming data within a warehouse using modular SQL and version control. It functions as a data transformation engine that enables users to define data structures and business logic through declarative configuration files, which the system then compiles into executable code. By managing complex data dependencies through a directed acyclic graph, it ensures that transformation tasks execute in the correct order while maintaining a manifest-driven state to track lineage and execution history.
The project distinguishes itself through an adapter-based database abstraction that translates generic transformation commands into dialect-specific SQL for various data warehouses. It utilizes a template engine to dynamically generate and inject SQL logic at runtime, allowing for highly flexible and reusable transformation scripts. Furthermore, it supports an incremental materialization strategy that optimizes performance by processing only new or changed records, merging them into existing tables using unique keys to reduce compute costs.
The framework covers the entire lifecycle of data transformation, including development, testing, deployment, and monitoring. It provides comprehensive capabilities for managing data lineage, enforcing code quality through automated linting and testing, and orchestrating complex pipelines across distributed environments. Users can also leverage a centralized semantic layer to define and govern business metrics, ensuring consistent data reporting across diverse analytical tools.
The project is distributed as a Python-based tool, providing a unified interface for local development that integrates with version control systems and cloud-based configuration management.
