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Dagster vs Airflow
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Data Engineering
Data Pipeline
Data Platform
August 22, 2025
Learn how to use the beta dbt Fusion engine in your Dagster pipelines, and the technical details of how support was added
August 20, 2025
Explore another set of powerful yet overlooked Python features—from overload and cached_property to contextvars and ExitStack
August 8, 2025
We are announcing the release of our MCP server, enabling AI assistants like Cursor to seamlessly integrate with Dagster projects through Model Context Protocol, unlocking composable workflows across your entire data stack.
August 7, 2025
A deep dive into how Dagster leverages pyproject.toml for modern Python packaging, from project metadata and dependencies to build systems and development tooling.
Software-Defined Assets are a new abstraction that allows data teams to focus on the end products, not just the individual tasks, in their data pipeline.
July 31, 2025
Python's clean syntax makes it easy to jump into unfamiliar codebases, but this simplicity often masks the intricate world of packaging that confuses many developers.
July 30, 2025
How dependency injection and smart resource management can save your sanity (and your deployments)
July 25, 2025
Setting up your Dagster project the right way from day one saves you headaches later, makes your team more effective, and helps scale.
July 23, 2025
Advanced Python features that AI agents may miss
July 10, 2025
Dagster is excited to announce the launch of ETL with Dagster, a comprehensive seven-lesson course. This free course guides you through practical ETL implementation and architectural considerations, from single-file ingestion to full-scale database replication
June 26, 2025
Significantly improved pipeline-building experience with Components and dg, enhanced orchestration capabilities, integration power-ups, and more.
June 17, 2025
Designing better data tooling with DSLs
June 12, 2025
How to organize your code locations for clarity, maintainability, and reuse.
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