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Breaking BAD: A Data Serving Vision for Big Active Data.

Michael J Carey1, Steven Jacobs2, Vassilis J Tsotras2

  • 1Univ. of California, Irvine.

Proceedings of the ... International Workshop on Distributed Event-Based Systems. International Workshop on Distributed Event-Based Systems
|October 17, 2017
PubMed
Summary
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This project introduces active Big Data platforms, moving beyond passive systems. The Big Active Data (BAD) system aims for continuous data capture and automatic information delivery for users and analysis.

Area of Science:

  • Computer Science
  • Data Science
  • Database Systems

Background:

  • Current Big Data systems are predominantly passive, reacting to queries rather than proactively serving information.
  • There is a need for systems that can automatically deliver timely information from Big Data streams.

Purpose of the Study:

  • To shift Big Data platforms from passive to active.
  • To detail a vision for a scalable Big Active Data (BAD) system.
  • To focus on the Data Serving component of the BAD system.

Main Methods:

  • Extending an existing scalable open-source Big Data Management System (BDMS), AsterixDB.
  • Developing a system for continuous and reliable Big Data capture.
  • Implementing timely and automatic delivery of new information.
Keywords:
Active DataBig DataParallel DatabasesPub/Sub

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Main Results:

  • Conceptualization and initial development of the Big Active Data (BAD) system.
  • Focus on the Data Serving piece, including key concepts and user model.
  • Laying the groundwork for a scalable active data platform.

Conclusions:

  • Active Big Data platforms offer a paradigm shift from passive systems.
  • The Big Active Data (BAD) system, built upon AsterixDB, is a promising approach.
  • The Data Serving component is crucial for enabling automatic information delivery.