Dagster has become the industry standard for orchestration of SQL transformations within a warehouse, particularly with its integration with dbt. The latest release (1.4) focuses on making Dagster's dbt integration more flexible and easier to get started. Unlike other general-purpose orchestrators like Airflow, Dagster's core design principles align well with dbt's approach to data pipelines, allowing for faithful orchestration of dbt models. Additionally, Dagster compensates for dbt's limitations by connecting the models in a dbt project to other kinds of data assets, such as tables ingested using tools like Fivetran or machine learning models. Dagster provides a full set of orchestration features, including flexible scheduling options, observability, partitioning, and alerting. The tool also allows for self-deployment on-premises, unlike dbt Cloud, which is a proprietary cloud service with no open-source equivalent. By using Dagster, teams can orchestrate their data pipelines more efficiently, ensuring that their data assets are materialized to meet their SLAs.