ECOS: Evolutionary Column-Oriented Storage

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.