Dagster is an open-source data orchestrator designed for building, managing, and monitoring data pipelines. It simplifies the process of creating reliable, reproducible data workflows that can scale across different environments, from local machines to production clusters, and integrates seamlessly with other data tools.

Features of Dagster:

• Unified system for orchestrating, scheduling, and monitoring data pipelines.
• Strong focus on data quality, versioning, and reproducibility.
• Built-in support for testing, validation, and deployment of pipelines.
• Dagster's " solids" and "pipelines" provide a powerful way to build modular and reusable workflows.
• Integrates with popular data tools such as DBT, Spark, and Airflow.
• End-to-end observability with logs, metrics, and rich visualizations to track the performance of pipelines.

To check Dagster version: dagster --version

Disclaimer: Dagster is an independent open-source project maintained by the Dagster team and the community. It is not affiliated with, endorsed by, or sponsored by Apache Airflow, Apache Spark, or other orchestration tools. It is provided "as is," without any warranty, express or implied. Users are responsible for understanding and complying with licensing terms, data policies, and regulations while deploying Dagster.