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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. Note: Bibliographic references for systems are not listed, but URLs for more information can be found in the System References table at the end of this paper. Caveat: Statements in this paper are based on sources and documentation that may not be reliable, and the systems described are “moving targets,” so some statements may be incorrect. Verify through other sources before depending on information here. Nevertheless, we hope this comprehensive survey is useful! Check for future corrections on the author’s web site cattell.net/datastores. Disclosure: The author is on the technical advisory board of Schooner Technologies and has a consulting business advising on scalable databases.