Self-tuning Database Systems: A Systematic Literature Review of Automatic Schema Design and Tuning

What is it about?

Self-tuning is a feature of autonomic databases that includes the problem of automatic schema design. It aims at providing an optimized schema that increases the overall database performance. While in relational databases automatic schema design focuses on the automated design of the physical schema, in NoSQL databases all levels of representation are considered: conceptual, logical, and physical. In this work, we carry out a systematic literature survey on automatic schema design in both SQL and NoSQL databases. We identify the levels of representation and the methods that are used for the schema design problem, and we present a novel taxonomy to classify and compare different schema design solutions.

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Why is it important?

our work is the first substantial effort to explore automatic schema tuning approaches in both SQL and NoSQL databases, as well as the first work to propose a taxonomy for evaluating and comparing different schema tuning solutions. This survey helps to investigate the gap between the motivations and capabilities of current solutions, and consequently to identify areas for future research.