Aurora: a new model and architecture for data stream management

  • Authors:

  • Daniel J. Abadi;Don Carney;Ugur Çetintemel;Mitch Cherniack;Christian Convey;Sangdon Lee;Michael Stonebraker;Nesime Tatbul;Stan Zdonik

  • Affiliations:

  • Department of Computer Science, Brandeis University, MA 02254, Waltham, USA;Department of Computer Science, Brown University, RI 02912, Providence, USA;Department of Computer Science, Brown University, RI 02912, Providence, USA;Department of Computer Science, Brandeis University, MA 02254, Waltham, USA;Department of Computer Science, Brown University, RI 02912, Providence, USA;Department of Computer Science, Brown University, RI 02912, Providence, USA;Department of EECS and Laboratory of Computer Science, M.I.T., MA 02139, Cambridge, USA;Department of Computer Science, Brown University, RI 02912, Providence, USA;Department of Computer Science, Brown University, RI 02912, Providence, USA

  • Venue:
  • The VLDB Journal — The International Journal on Very Large Data Bases
  • Year:
  • 2003

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Abstract

Abstract.This paper describes the basic processing model and architecture of Aurora, a new system to manage data streams for monitoring applications. Monitoring applications differ substantially from conventional business data processing. The fact that a software system must process and react to continual inputs from many sources (e.g., sensors) rather than from human operators requires one to rethink the fundamental architecture of a DBMS for this application area. In this paper, we present Aurora, a new DBMS currently under construction at Brandeis University, Brown University, and M.I.T. We first provide an overview of the basic Aurora model and architecture and then describe in detail a stream-oriented set of operators.