数据存储方案

引言

文献是由Rick Cattell撰写的论文，论文讨论了可扩展的结构化数据的、非结构化的（包括基于键值对的、基于文档的和面向列的）数据存储方案（注：NOSQL 是支撑大数据应用的关键所在。事实上，将NOSQL翻译为“非结构化”不甚准确，因为NOSQL更为常见的解释是：Not Only SQL（不仅仅是结构化），换句话说，NOSQL并不是站在结构化SQL的对立面，而是既可包括结构化数据，也可包括非结构化数据）。

论文信息

Scalable SQL and NoSQL Data Stores

Rick Cattell Originally published in 2010, last revised December 2011

摘要

ABSTRACT

In this paper, we examine a number of SQL and so- called ―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.

在这篇文献中，我们验证了许多SQL和所谓的‗NoSQL‘数据存储（它设计于支持简单的OLTP风格的应用，能够用于扩展在很多服务器上）

它最先由Web 2.0应用引起，与传统的数据库管理系统和数据仓库对比，这些系统设计为可扩展到数以千计或数以百万计的用户做更新，同时读取。

我们对比了新系统上的数据模型，一致性机制, 存储机制，持久性保证，可用性，支持的查询以及其它属性，这些系统典型的牺牲（为了实现其它属性而去掉）了一些属性。如数据库常有的事务一致性，牺牲了这个是为了其它的属性，如高可用，可扩展。

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.

注：参考书没列出来（翻译省）

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 /datastores.

警告：一些提及的书可能不可用。尽管如此，我们还是希望这篇综合的文献对大家有帮助，我们网站：/datastores.

Disclosure: The author is on the technical advisory board of Schooner Technologies and has a consulting business advising on scalable databases.

透漏：作者是可扩展数据库商业顾问。

1. OVERVIEW

In recent years a number of new systems have been designed to provide good horizontal scalability for simple read/write database operations distributed over many servers. In contrast, traditional database products have comparatively little or no ability to scale horizontally on these applications. This paper examines and compares the various new systems.

近年，很多系统的设计提供良好水平扩展，支持在多服务器上分布式读写。相比较传统的系统，一般为无扩展，规模小。

本篇文献研究与对比很多不同的新系统（Yol注，其实就是各种NOSQL设计进行对比，比如Mongo与Hbase分类，简介）

Many of the new systems are referred to as ―NoSQL‖ data stores. The definition of NoSQL, which stands for ―Not Only SQL‖ or ―Not Relational‖, is not entirely agreed upon. For the purposes of this paper, NoSQL systems generally have six key features: NoSQL等于Not Only SQL, 或者Not Relational(弱关系型数据库，与mysql比较

起来)，NoSQL的systems一般有6重要特征：

1. the ability to horizontally scale ―simple operation‖ throughput over many servers,

通过简单操作在多服务器上水平扩展的能力

2. the ability to replicate and to distribute (partition) data over many servers,

复制和分发(分区) 数据在多个服务器的能力

3. a simple call level interface or protocol (in contrast to a SQL binding),

一种简单的调用级接口或协议(相比较于SQL 绑定)