SIGMOD '85 Proceedings of the 1985 ACM SIGMOD international conference on Management of data
ACM Transactions on Database Systems (TODS)
Fractal prefetching B+-Trees: optimizing both cache and disk performance
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
The case for the reduced instruction set computer
ACM SIGARCH Computer Architecture News
Implementation Techniques of Complex Objects
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
Foundations of automated database tuning
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Integrating compression and execution in column-oriented database systems
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Automatic physical design tuning: workload as a sequence
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Efficient use of the query optimizer for automated physical design
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Column-stores vs. row-stores: how different are they really?
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Read-optimized databases, in depth
Proceedings of the VLDB Endowment
Automated physical design in database caches
ICDEW '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering Workshop
HOBI: Hierarchically Organized Bitmap Index for Indexing Dimensional Data
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
Using evolving storage structures for data storage
Proceedings of the 8th International Conference on Frontiers of Information Technology
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As DBMS has grown more powerful over the last decades, they have also become more complex to manage. To achieve efficiency by DBMS tuning is nowadays a hard task carried out by experts. This development inspired the ongoing research on self-tuning to make DBMS more easily manageable. We present a customizable self-tuning storage manager, we termed as Evolutionary Column-Oriented Storage (ECOS). The capability of self-tuning data management with minimal human intervention, which is the main design goal for ECOS, is achieved by dynamically adjusting the storage structures of a column-oriented storage manager according to data size and access characteristics. ECOS is based on the Decomposed Storage Model (DSM). It supports customization at the table-level using five different variations of DSM. ECOS also proposes fine-grained customization of storage structures at the column-level. It uses hierarchically-organized storage structures for each column, which enables autonomic selection of the suitable storage structure along the hierarchy using an evolution mechanism (as hierarchy-level increases). Moreover, for ECOS, we proposed the concept of an evolution path that provides a reduction of human intervention for database maintenance. We evaluated ECOS empirically using a custom micro benchmark showing performance improvement.