Wide area placement of data replicas for fast and highly available data access

Ping, Fan; Hwang, Jeong-Hyon; Li, Xiaohu; McConnell, Chris; Vabbalareddy, Rohini

doi:10.1145/1996014.1996016

Cited by 5 publications

(1 citation statement)

References 17 publications

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“…Several papers have considered how to place data in a geo-distributed cluster. Some [2,9,48,58,77] minimize transaction latency while maximizing availability, adhering to fault tolerance requirements, and/or balancing load. Others [40,74] minimize cost while adhering to latency SLOs.…”

Section: Related Workmentioning

confidence: 99%

CockroachDB: The Resilient Geo-Distributed SQL Database

Taft¹,

Sharif²,

Matei³

et al. 2020

Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data

127

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We live in an increasingly interconnected world, with many organizations operating across countries or even continents. To serve their global user base, organizations are replacing their legacy DBMSs with cloud-based systems capable of scaling OLTP workloads to millions of users.CockroachDB is a scalable SQL DBMS that was built from the ground up to support these global OLTP workloads while maintaining high availability and strong consistency. Just like its namesake, CockroachDB is resilient to disasters through replication and automatic recovery mechanisms.This paper presents the design of CockroachDB and its novel transaction model that supports consistent geo-distributed transactions on commodity hardware. We describe how CockroachDB replicates and distributes data to achieve fault tolerance and high performance, as well as how its distributed SQL layer automatically scales with the size of the database cluster while providing the standard SQL interface that users expect. Finally, we present a comprehensive performance evaluation and share a couple of case studies of CockroachDB users. We conclude by describing lessons learned while building CockroachDB over the last five years.

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Section: Related Workmentioning

confidence: 99%