Leanstore: in-memory data management beyond main memory

Viktor Leis, Michael Haubenschild, Alfons Kemper, Thomas Neumann

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

78 Zitate (Scopus)

Abstract

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.

OriginalspracheEnglisch
TitelProceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten185-196
Seitenumfang12
ISBN (elektronisch)9781538655207
DOIs
PublikationsstatusVeröffentlicht - 24 Okt. 2018
Veranstaltung34th IEEE International Conference on Data Engineering, ICDE 2018 - Paris, Frankreich
Dauer: 16 Apr. 201819 Apr. 2018

Publikationsreihe

NameProceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018

Konferenz

Konferenz34th IEEE International Conference on Data Engineering, ICDE 2018
Land/GebietFrankreich
OrtParis
Zeitraum16/04/1819/04/18

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