@Scout do input managers improve performance?

Yes, IO Managers in Dagster can improve performance by managing how data is read from and written to persistent storage. They allow you to separate the code responsible for logical data transformations from the code that handles the reading and writing of results. This separation can lead to more efficient and maintainable pipelines. For example, the documentation mentions that we have updated the Snowflake, DuckDB, and BigQuery integrations, adding partition support to the IO Managers. This support for partitions can improve performance by enabling more efficient data loading and querying. The IO Managers have also been updated to support various types of partitions, such as static partitions, time window partitions, multi-partitions, and dynamic partitions (coming soon). These features can help optimize data access patterns and reduce unnecessary data processing, which can lead to performance improvements. Additionally, IO Managers can be configured to handle specific storage backends or data formats, which can also contribute to performance gains by leveraging the strengths of the underlying storage systems and minimizing data conversion overhead. In summary, by providing a flexible and configurable way to manage data input and output, IO Managers can play a significant role in improving the performance of Dagster pipelines.