Fractal prefetching B+-Trees: optimizing both cache and disk performance
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
IEEE Micro
A Study of Index Structures for Main Memory Database Management Systems
VLDB '86 Proceedings of the 12th International Conference on Very Large Data Bases
Rethinking Database System Architecture: Towards a Self-Tuning RISC-Style Database System
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
ATEC '99 Proceedings of the annual conference on USENIX Annual Technical Conference
HOBI: Hierarchically Organized Bitmap Index for Indexing Dimensional Data
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
ECOS: evolutionary column-oriented storage
BNCOD'11 Proceedings of the 28th British national conference on Advances in databases
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Different data storage structures suit different data management scenarios, therefore, a universal data storage structure is not possible. Furthermore, each data storage structure has different resource consumption because of their unique execution complexity. Self-tuning data management systems need a mechanism to select appropriate data storage structure and to adapt it with changing data management requirements. We propose Evolving Storage Structures for self-tuning data management system that supports customization and adaptation with changing data management needs.