Rick Cattell
Abstract
In this paper, we examine a number of SQL and socalled "NoSQL" data stores designed to scale simple OLTP-style application loads over many servers. Originally motivated by Web 2.0 applications, these systems are designed to scale to thousands or millions of users doing updates as well as reads, in contrast to traditional DBMSs and data warehouses. We contrast the new systems on their data model, consistency mechanisms, storage mechanisms, durability guarantees, availability, query support, and other dimensions. These systems typically sacrifice some of these dimensions, e.g. database-wide transaction consistency, in order to achieve others, e.g. higher availability and scalability.
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Digital Library
- B. Cooper et al, "Benchmarking Cloud Serving Systems with YCSB", ACM Symposium on Cloud Computing (SoCC), Indianapolis, Indiana, June 2010. Google ScholarDigital Library
- B. DeCandia et al, "Dynamo: Amazon's Highly Available Key-Value Store", Proceedings 21st ACM SIGOPS Symposium on Operating Systems Principles, 2007. Google ScholarDigital Library
- S. Gilbert and N. Lynch, "Brewer's conjecture and the feasibility of consistent, available, and partition-tolerant web services", ACM SIGACT News 33, 2, pp 51--59, March 2002. Google ScholarDigital Library
- M. Stonebraker and R. Cattell, "Ten Rules for Scalable Performance in Simple Operation Datastores", Communications of the ACM, June 2011. Google ScholarDigital Library
Index Terms
- Scalable SQL and NoSQL data stores
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