SQL Query to Trigger Translation: A Novel Transparent Consistency Technique for Cache Augmented SQL Systems

Abstract

Organizations enhance the velocity of simple operations that read and write a small amount of data from big data by extending a SQL system with a key-value store (KVS). The resulting system is suitable for workloads that issue simple operations and exhibit a high read to write ratio, e.g., interactive social networking actions. A popular distributed in-memory KVS is memcached in use by organizations such as Facebook and YouTube. This study presents SQL query to trigger translation (SQLTrig) as a novel transparent consistency technique that maintains the key-value pairs of the KVS consistent with the tabular data in the relational database management system (RDBMS). SQLTrig provides physical data independence, hiding the representation of data (either as rows of a table or key-value pairs) from the application developers. Software developers are provided with the SQL query language and observe the performance enhancements of a KVS without authoring additional software. This simplifies software complexity to expedite its development life cycle.