ASTERIX: an open source system for "Big Data" management and analysis (demo)

Authors:
Sattam Alsubaiee;Yasser Altowim;Hotham Altwaijry;Alexander Behm;Vinayak Borkar;Yingyi Bu;Michael Carey;Raman Grover;Zachary Heilbron;Young-Seok Kim;Chen Li;Nicola Onose;Pouria Pirzadeh;Rares Vernica;Jian Wen
Affiliations:
University of California, Irvine;University of California, Irvine;University of California, Irvine;University of California, Irvine;University of California, Irvine;University of California, Irvine;University of California, Irvine;University of California, Irvine;University of California, Irvine;University of California, Irvine;University of California, Irvine;Google;University of California, Irvine;HP Labs;University of California, Riverside
Venue:
Proceedings of the VLDB Endowment
Year:
2012

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Abstract

At UC Irvine, we are building a next generation parallel database system, called ASTERIX, as our approach to addressing today's "Big Data" management challenges. ASTERIX aims to combine time-tested principles from parallel database systems with those of the Web-scale computing community, such as fault tolerance for long running jobs. In this demo, we present a whirlwind tour of ASTERIX, highlighting a few of its key features. We will demonstrate examples of our data definition language to model semi-structured data, and examples of interesting queries using our declarative query language. In particular, we will show the capabilities of ASTERIX for answering geo-spatial queries and fuzzy queries, as well as ASTERIX' data feed construct for continuously ingesting data.