- Titel
- Integer Compression in NVRAM-centric Data Stores
- Untertitel
- Comparative Experimental Analysis to DRAM
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-805474
- Konferenz
- SIGMOD/PODS '19: International Conference on Management of Data. Amsterdam, 1. Juli 2019
- Quellenangabe
- DaMoN'19: Proceedings of the 15th International Workshop on Data Management on New Hardware
Herausgeber: Association for Computing Machinery
Erscheinungsort: New York
Verlag: ACM
Erscheinungsjahr: 2019
Seiten: 1-11
ISBN: 978-1-4503-6801-8
Artikelnummer: 11 - Erstveröffentlichung
- 2019
- Abstract (EN)
- Lightweight integer compression algorithms play an important role in in-memory database systems to tackle the growing gap between processor speed and main memory bandwidth. Thus, there is a large number of algorithms to choose from, while different algorithms are tailored to different data characteristics. As we show in this paper, with the availability of byte-addressable non-volatile random-access memory (NVRAM), a novel type of main memory with specific characteristics increases the overall complexity in this domain. In particular, we provide a detailed evaluation of state-of-the-art lightweight integer compression schemes and database operations on NVRAM and compare it with DRAM. Furthermore, we reason about possible deployments of middle- and heavyweight approaches for better adaptation to NVRAM characteristics. Finally, we investigate a combined approach where both volatile and non-volatile memories are used in a cooperative fashion that is likely to be the case for hybrid and NVRAM-centric database systems.
- Andere Ausgabe
- Link zum Artikel, der zuerst in der ACM Digital Library erschienen ist.
DOI: 10.1145/3329785.3329923 - Freie Schlagwörter (DE)
- In-Memory, Datenkompression; Nvram, Analyse, Datenbanksysteme
- Freie Schlagwörter (EN)
- in-memory, data compression, nvram; analysis, database systems
- Klassifikation (DDC)
- 004
- Verlag
- ACM, New York
- Förder- / Projektangaben
- Deutsche Forschungsgemeinschaft (DFG)
Sachbeihilfen
Self-Recoverable and Highly Available Data Structures for NVRAM-centric Database Systems
ID: 318788683
Deutsche Forschungsgemeinschaft (DFG)
Sonderforschungsbereich
HAEC - Highly Adaptive Energy-Efficient Computing (SFB 912)
ID: 164481002 - Version / Begutachtungsstatus
- angenommene Version / Postprint / Autorenversion
- URN Qucosa
- urn:nbn:de:bsz:14-qucosa2-805474
- Veröffentlichungsdatum Qucosa
- 01.09.2022
- Dokumenttyp
- Konferenzbeitrag
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
