PBS at work: advancing data management with consistency metrics

Authors:
Peter Bailis;Shivaram Venkataraman;Michael J. Franklin;Joseph M. Hellerstein;Ion Stoica
Affiliations:
UC Berkeley, Berkeley, CA, USA;UC Berkeley, Berkeley, CA, USA;UC Berkeley, Berkeley, CA, USA;UC Berkeley, Berkeley, CA, USA;UC Berkeley, Berkeley, CA, USA
Venue:
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Year:
2013

Citing 8
Cited 0

Consistency in a partitioned network: a survey

ACM Computing Surveys (CSUR)
Design and evaluation of a conit-based continuous consistency model for replicated services

ACM Transactions on Computer Systems (TOCS)
Eventually consistent

Communications of the ACM - Rural engineering development
Unsupervised modeling of Twitter conversations

HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Analyzing consistency properties for fun and profit

Proceedings of the 30th annual ACM SIGACT-SIGOPS symposium on Principles of distributed computing
Probabilistically bounded staleness for practical partial quorums

Proceedings of the VLDB Endowment
Consistency Tradeoffs in Modern Distributed Database System Design: CAP is Only Part of the Story

Computer
Toward a principled framework for benchmarking consistency

HotDep'12 Proceedings of the Eighth USENIX conference on Hot Topics in System Dependability

Quantified Score

Hi-index	0.00

Visualization

Abstract

A large body of recent work has proposed analytical and empirical techniques for quantifying the data consistency properties of distributed data stores. In this demonstration, we begin to explore the wide range of new database functionality they enable, including dynamic query tuning, consistency SLAs, monitoring, and administration. Our demonstration will exhibit how both application programmers and database administrators can leverage these features. We describe three major application scenarios and present a system architecture for supporting them. We also describe our experience in integrating Probabilistically Bounded Staleness (PBS) predictions into Cassandra, a popular NoSQL store and sketch a demo platform that will allow SIGMOD attendees to experience the importance and applicability of real-time consistency metrics.