Building a Data Management System for the Cloud: Lessons Learned and Future Directions

Abstract The paper discusses the lessons learned from building Snowflake, a data management system for the cloud. Given the need for systems that can scale to handle large data volumes, provide expressive programming interfaces, and leverage the benefits of cloud computing, it describes the architecture of a cloud-based data management system and optimization techniques specific to the cloud. Key techniques include pruning large file sets at both compile time and query runtime, optimizing data layouts in the background, and, more generally, the importance of performing maintenance tasks in the background, which is enabled by cloud resources. The paper also explains the need for using immutable files and the implications for data modification queries. Finally, it highlights the operational aspects of building and maintaining a data management system that functions as an online cloud service. The paper concludes by outlining future directions for cloud-based data management systems.