Dagster
Orchestration platform for data assets
Dagster is an open-source data orchestration platform that is designed to help data engineers and scientists build, test, and deploy data pipelines. It provides a range of features for building and managing complex data workflows, and is specifically designed to handle data processing tasks that involve a large number of dependencies. Dagster's core features include: Pipeline Modeling: Dagster provides a flexible pipeline modeling system that enables users to create complex data workflows using a simple, intuitive syntax. The pipeline modeling system includes support for tasks, dependencies, and inputs and outputs. Data Validation: Dagster provides a robust data validation system that helps users ensure that the data flowing through their pipelines is valid and meets the required specifications. This includes support for schema validation, type checking, and custom validation rules. Testing: Dagster provides a powerful testing framework that makes it easy for users to test their data pipelines and ensure that they are working as expected. The testing framework includes support for unit testing, integration testing, and end-to-end testing. Deployment: Dagster provides a range of deployment options, including support for running pipelines on a local machine, on a server, or in a cloud environment. It also includes support for running pipelines on a schedule or in response to events. Monitoring and Alerting: Dagster provides a range of monitoring and alerting features that help users track the health and performance of their data pipelines. This includes support for logging, metrics, and alerts. Extensibility: Dagster is designed to be easily extensible and customizable. Developers can create their own pipeline components, plugins, and integrations, or modify the core platform to meet their specific needs. Overall, Dagster is a powerful and flexible data orchestration platform that is ideal for data engineers and scientists who need to build, test, and deploy complex data pipelines. Its flexible pipeline modeling system, robust data validation and testing features, and extensive deployment options make it a popular choice for data-intensive applications. Its extensibility and open-source nature also make it a great choice for users who want to customize the platform to meet their specific needs.