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Dagster
Dagster is an open-source data orchestration platform designed to help data engineers and scientists build, test, and monitor data pipelines.
Dagster is an open-source data orchestration platform designed to help data engineers and scientists build, test, and monitor data pipelines. It provides a flexible Python API for defining data workflows, allowing users to create modular, reusable components called "assets" that represent data artifacts or computational steps. Dagster emphasizes data lineage and observability, enabling users to track the relationships between different data assets and understand how changes propagate through the system.
The platform supports various execution environments, including local development, containerized deployments, and cloud-native setups. Dagster integrates seamlessly with popular data tools and frameworks like Pandas, Spark, and dbt, making it easier to incorporate existing data processes into a unified workflow.
Related terms
Data orchestration →
Data orchestration is the automated coordination, scheduling, and monitoring of interdependent data tasks—such as extracts, transformations, and loads—so they run in the correct order and recover cleanly from failure.
pipelines →Data pipelines are automated workflows that move and transform data from various sources to one or more destinations.
dbt →dbt (data build tool) is an open-source command-line tool that enables data analysts and engineers to transform data in their warehouses more effectively.
data build tool (dbt) →dbt is an open-source command-line tool that enables data analysts and engineers to transform data in their warehouses more effectively.
MotherDuck →MotherDuck is a cloud-based analytics platform built on top of DuckDB that enables teams to analyze and share data without managing complex infrastructure.
GitHub →GitHub is a web-based platform for version control and collaboration, widely used in software development and data engineering.
