Towards a One Size Fits All Database Architecture.

TLDR: This work proposes a new type of database system coined OctopusDB, which uses a logical event log as its primary storage structure and introduces the concept of Storage Views (SV), i.e. secondary, alternative physical data representations covering all or subsets of the primary log.

Abstract: We propose a new type of database system coined OctopusDB. Our approach suggests a unified, one size fits all data processing architecture for OLTP, OLAP, streaming systems, and scan-oriented database systems. OctopusDB radically departs from existing architectures in the following way: it uses a logical event log as its primary storage structure. To make this approach efficient we introduce the concept of Storage Views (SV), i.e. secondary, alternative physical data representations covering all or subsets of the primary log. OctopusDB (1) allows us to use different types of SVs for different subsets of the data; and (2) eliminates the need to use different types of database systems for different applications. Thus, based on the workload, OctopusDB emulates different types of systems (row stores, column stores, streaming systems, and more importantly, any hybrid combination of these). This is a feature impossible to achieve with traditional DBMSs.