TY - GEN
T1 - Leanstore
T2 - 34th IEEE International Conference on Data Engineering, ICDE 2018
AU - Leis, Viktor
AU - Haubenschild, Michael
AU - Kemper, Alfons
AU - Neumann, Thomas
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/24
Y1 - 2018/10/24
N2 - Disk-based database systems use buffer managers in order to transparently manage data sets larger than main memory. This traditional approach is effective at minimizing the number of I/O operations, but is also the major source of overhead in comparison with in-memory systems. To avoid this overhead, in-memory database systems therefore abandon buffer management altogether, which makes handling data sets larger than main memory very difficult. In this work, we revisit this fundamental dichotomy and design a novel storage manager that is optimized for modern hardware. Our evaluation, which is based on TPC-C and micro benchmarks, shows that our approach has little overhead in comparison with a pure in-memory system when all data resides in main memory. At the same time, like a traditional buffer manager, it is fully transparent and can manage very large data sets effectively. Furthermore, due to low-overhead synchronization, our implementation is also highly scalable on multi-core CPUs.
AB - Disk-based database systems use buffer managers in order to transparently manage data sets larger than main memory. This traditional approach is effective at minimizing the number of I/O operations, but is also the major source of overhead in comparison with in-memory systems. To avoid this overhead, in-memory database systems therefore abandon buffer management altogether, which makes handling data sets larger than main memory very difficult. In this work, we revisit this fundamental dichotomy and design a novel storage manager that is optimized for modern hardware. Our evaluation, which is based on TPC-C and micro benchmarks, shows that our approach has little overhead in comparison with a pure in-memory system when all data resides in main memory. At the same time, like a traditional buffer manager, it is fully transparent and can manage very large data sets effectively. Furthermore, due to low-overhead synchronization, our implementation is also highly scalable on multi-core CPUs.
KW - SSD
KW - in memory
KW - storage engine
UR - http://www.scopus.com/inward/record.url?scp=85052403883&partnerID=8YFLogxK
U2 - 10.1109/ICDE.2018.00026
DO - 10.1109/ICDE.2018.00026
M3 - Conference contribution
AN - SCOPUS:85052403883
T3 - Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018
SP - 185
EP - 196
BT - Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 16 April 2018 through 19 April 2018
ER -