Towards scalable real-time analytics: An architecture for scale-out of OLxP workloads

Research output: Contribution to book/Conference proceedings/Anthology/ReportChapter in book/Anthology/ReportContributedpeer-review

Contributors

  • Anil K. Goel - , SAP SE Canada (Author)
  • Jeffrey Pound - , SAP SE Canada (Author)
  • Nathan Auch - , SAP SE Canada (Author)
  • Peter Bumbulis - , SAP SE Canada (Author)
  • Scott MacLean - , SAP SE Canada (Author)
  • Franz Färber - , SAP Research (Author)
  • Francis Gropengiesser - , SAP Research (Author)
  • Christian Mathis - , SAP Research (Author)
  • Thomas Bodner - , SAP Research (Author)
  • Wolfgang Lehner - , Chair of Databases (Author)

Abstract

We present an overview of our work on the SAP HANA Scale-out Extension, a novel distributed database architecture designed to support large scale analytics over realtime data. This platform permits high performance OLAP with massive scale-out capabilities, while concurrently allowing OLTP workloads. This dual capability enables analytics over real-time changing data and allows fine grained userspecifi ed service level agreements (SLAs) on data freshness. We advocate the decoupling of core database components such as query processing, concurrency control, and persistence, a design choice made possible by advances in highthroughput low-latency networks and storage devices. We provide full ACID guarantees and build on a logical timestamp mechanism to provide MVCC-based snapshot isolation, while not requiring synchronous updates of replicas. Instead, we use asynchronous update propagation guaranteeing consistency with timestamp validation. We provide a view into the design and development of a large scale data management platform for real-time analytics, driven by the needs of modern enterprise customers.

Details

Original languageEnglish
Title of host publicationProceedings of the 41st International Conference on Very Large Data Bases, Kohala Coast, Hawaii
EditorsChristophe Claramunt, Simonas Saltenis, Ki-Joune Li
PublisherAssociation for Computing Machinery
Pages1716-1727
Number of pages12
Publication statusPublished - 2015
Peer-reviewedYes

Publication series

SeriesProceedings of the VLDB Endowment
Number12
Volume8
ISSN2150-8097

Conference

Title3rd Workshop on Spatio-Temporal Database Management, STDBM 2006, Co-located with the 32nd International Conference on Very Large Data Bases, VLDB 2006
Duration11 September 2006
CitySeoul
CountryKorea, Republic of

External IDs

ORCID /0000-0001-8107-2775/work/198592325