Retrospective on Aurora

  • Authors:

  • Hari Balakrishnan;Magdalena Balazinska;Don Carney;Uğur Çetintemel;Mitch Cherniack;Christian Convey;Eddie Galvez;Jon Salz;Michael Stonebraker;Nesime Tatbul;Richard Tibbetts;Stan Zdonik

  • Affiliations:

  • Department of EECS and Laboratory of Computer Science, Massachussetts Institute of Technology, USA;Department of EECS and Laboratory of Computer Science, Massachussetts Institute of Technology, USA;Department of Computer Science, Brown University, USA;Department of Computer Science, Brown University, USA;Department of Computer Science, Brandeis University, USA;Department of Computer Science, Brown University, USA;Department of Computer Science, Brandeis University, USA;Department of EECS and Laboratory of Computer Science, Massachussetts Institute of Technology, USA;Department of EECS and Laboratory of Computer Science, Massachussetts Institute of Technology, USA;Department of Computer Science, Brown University, USA;Department of EECS and Laboratory of Computer Science, Massachussetts Institute of Technology, USA;Department of Computer Science, Brown University, USA

  • Venue:
  • The VLDB Journal — The International Journal on Very Large Data Bases
  • Year:
  • 2004

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Abstract

This experience paper summarizes the key lessons we learned throughout the design and implementation of the Aurora stream-processing engine. For the past 2 years, we have built five stream-based applications using Aurora. We first describe in detail these applications and their implementation in Aurora. We then reflect on the design of Aurora based on this experience. Finally, we discuss our initial ideas on a follow-on project, called Borealis, whose goal is to eliminate the limitations of Aurora as well as to address new key challenges and applications in the stream-processing domain.