TY - GEN
T1 - NVDIMM-N Persistent Memory and its Impact on Two Relational Databases
AU - Katzburg, Netanel
AU - Golander, Amit
AU - Weiss, Shlomo
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - The architecture of Database Management Systems (DBMS) is closely related to the characteristics of the storage hierarchy, because durability and response time are highly dependent on the physical properties of the target storage. Main memory volatility requires a DBMS to provide durability by software means as data continuously moves between volatile memory buffers and input/output persistent media. In traditional storage systems applications use complex concurrency control schemes to reduce latency and increase throughput and in order to utilize multicore hardware and shared system resources. New persistent memory (PM) devices emerging in the last decade, such as PCM, RRAM and MRAM, exhibit near-DRAM speed and characteristics, provide data persistence, and could be game changing for storage bound applications. In this paper we focus on benefits of persistent memory and their impact on database management systems. We consider methods for application speedup that are applicable to DBMSs that use PM. These optimization methods depend on the characteristics of PM storage. We consider concurrency and mutual resource contention, explore and rethink major application components, and finally combine static code optimization. Running the on-line transaction processing (OLTP) workload, the DBMSs explored here show performance gains relative to traditional storage systems by a factor of 3.17 and 1.79 for PostgreSQL and SQLite respectively.
AB - The architecture of Database Management Systems (DBMS) is closely related to the characteristics of the storage hierarchy, because durability and response time are highly dependent on the physical properties of the target storage. Main memory volatility requires a DBMS to provide durability by software means as data continuously moves between volatile memory buffers and input/output persistent media. In traditional storage systems applications use complex concurrency control schemes to reduce latency and increase throughput and in order to utilize multicore hardware and shared system resources. New persistent memory (PM) devices emerging in the last decade, such as PCM, RRAM and MRAM, exhibit near-DRAM speed and characteristics, provide data persistence, and could be game changing for storage bound applications. In this paper we focus on benefits of persistent memory and their impact on database management systems. We consider methods for application speedup that are applicable to DBMSs that use PM. These optimization methods depend on the characteristics of PM storage. We consider concurrency and mutual resource contention, explore and rethink major application components, and finally combine static code optimization. Running the on-line transaction processing (OLTP) workload, the DBMSs explored here show performance gains relative to traditional storage systems by a factor of 3.17 and 1.79 for PostgreSQL and SQLite respectively.
KW - Data storage systems
KW - NVM-based file system
KW - PM-based file system
KW - file systems
KW - nonvolatile memory
KW - postgreSQL
KW - sQLite
UR - http://www.scopus.com/inward/record.url?scp=85063133043&partnerID=8YFLogxK
U2 - 10.1109/ICSEE.2018.8646020
DO - 10.1109/ICSEE.2018.8646020
M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???
AN - SCOPUS:85063133043
T3 - 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018
BT - 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018
Y2 - 12 December 2018 through 14 December 2018
ER -