ACM SIGMOD Record · 2011 · 1.3K citations · 5 references
ComputingComputer ScienceData ManagementDatabasesStorage SystemsData Storage SystemsDatabase ManagementNosql DatabasesQuery ProcessingScalable Data StorageStorage ScalabilityConsistencyData Storage MechanismsDatabase ScalabilityScalable Data ManagementScalable Database ArchitectureScalable Database SystemsScalable Storage SystemsWeb 2.0
Web 2.0 applications motivated the design of SQL and NoSQL data stores that scale to millions of users performing updates and reads, sacrificing database‑wide transaction consistency to achieve higher availability and scalability compared to traditional DBMSs and data warehouses. The study examines a range of SQL and NoSQL data stores that aim to scale simple OLTP‑style application loads across many servers. The authors compare these systems across dimensions such as data model, consistency, storage, durability, availability, and query support.
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.
5
Benchmarking cloud serving systems with YCSB
Brian F. Cooper, Adam Silberstein, Erwin Tam et al. · 2010 · 3.6K citations
Giuseppe DeCandia, Deniz Hastorun, Madan Jampani et al. · 2007 · 3.5K citations
Bigtable: a distributed storage system for structured data
Fay W. Chang, Jay B. Dean, Sanjay Ghemawat et al. · 2006 · 2K citations