Performance comparison of in-memory and disk-based databases using transaction processing performance council (TPC) benchmarking

Database performance throughput is one of the main measurements of the application effectiveness or a system, in terms of speed and delivery. Higher application efficiency is always a goal for any organization; therefore, finding the way to improve the database performance has priority. There are two main factors that can contribute to performance gain or slowness. Firstly, how well designed the database structure is in terms of data types, referential integrity, and indexes. Secondly, the underlying hardware infrastructure that consists of a server, storage, and network. During the application design lifecycle, the database schema is one area that continuously evolves. There are numerous configurational parameters that need to be adjusted according to database schema design and underlying infrastructure, in which in-memory is an important feature. In-memory database stores all data in physical memory, because of keeping entire data and changes of data in physical memory, the in-memory database provides very short response time and transactional throughput as compared to the disk-based database. This study provides comparison between in-memory and disk-based performance with impact analysis of concurrent users and parallelism using TPC-C benchmarking. A comprehensive benchmark guideline benefits for specific database environment was provided in order to track performance changes while migrating to in-memory from disk-based database. These benchmarking statistics provided comparative standpoint that can be verified during performance bottleneck. This study shows that transitioning from disk-based database to in-memory database decreased the response time and reduced the lock contention, however, requires detailed review for index design changes. Key words: Microsoft Structured Query Language (SQL) Server, in-memory, disk-based, transaction processing performance council (TPC-C), benchmarking, database performance, performance comparison, response time, parallelism, concurrent users.