1. Execution Model: Dagster provides a structured data pipeline execution model that allows for easy testing and orchestration of complex workflows, while Requests is a simple HTTP library for making requests and handling responses.
2. Error Handling: Dagster offers robust error handling and recovery mechanisms, enabling users to define how errors are handled within the pipeline, whereas Requests primarily deals with error handling at the request level.
3. Dependency Management: Dagster allows for easy management of dependencies between different parts of the pipeline, ensuring proper execution order and data flow, while Requests focuses on sending HTTP requests and receiving responses without the concept of dependencies.
4. Orchestration: Dagster provides tools for orchestrating and scheduling data pipelines, making it suitable for building and managing production-grade workflows, whereas Requests lacks built-in support for orchestration.
5. Extensions and Integrations: Dagster offers a wide range of built-in integrations with tools like databases, cloud services, and monitoring systems, enhancing its functionality, which is not a primary focus of Requests.
6. Data Processing Capabilities: Dagster includes features for processing, transforming, and analyzing data within the pipeline itself, while Requests is focused on the communication aspects of data retrieval from APIs.

In Summary, Dagster and Requests differ in their approach to data pipeline execution, error handling, dependency management, orchestration capabilities, integrations, and data processing features.