下一代数据库 [英] The Next-gen Databases

问题描述

我正在学习传统的关系数据库（使用 PostgreSQL ），并进行一些研究，我遇到了一些新类型的数据库。 CouchDB ，毛毛雨和 Scalaris 中列出了几个，将会是下一个数据库技术来处理？

I'm learning traditional Relational Databases (with PostgreSQL) and doing some research I've come across some new types of databases. CouchDB, Drizzle, and Scalaris to name a few, what is going to be the next database technologies to deal with?

推荐答案

gen SQL。

SQL是查询和操作关系数据库的语言。 SQL由国际标准规定。虽然标准被修订，似乎总是在关系数据库范例内工作。

SQL is a language for querying and manipulating relational databases. SQL is dictated by an international standard. While the standard is revised, it seems to always work within the relational database paradigm.

这里有一些新的数据存储技术，目前越来越受到关注：

Here are a few new data storage technologies that are getting attention currently:

• CouchDB 是一个非关系数据库。他们称之为面向文档的数据库。


• Amazon SimpleDB 也是以分布式方式通过Web服务访问的非关系数据库。亚马逊还有一个名为 Dynamo 的分布式键值存储，它可以管理其部分S3服务。


• Dynomite 和 Kai 是受Amazon Dynamo启发的开源解决方案。


• BigTable 是Google使用的专有数据存储解决方案，并且使用其Google文件系统技术实现。 Google的MapReduce框架使用BigTable。


• Hadoop / a>是一种源自Google MapReduce的开源技术，可满足类似的需求，可分发大规模数据存储的工作。


• Scalaris 是一个分布式事务键/值存储。也不是关系型的，不使用SQL。这是来自德国柏林的Zuse学院的一个研究项目。


• RDF 是用于存储语义数据的标准，其中数据和元数据可互换。它有自己的查询语言SPARQL，其表面上类似于SQL，但实际上完全不同。


• Vertica 是一个高度可扩展的面向列的分析数据库，专为分布式（网格）架构而设计。它声称是关系和SQL兼容。它可以通过Amazon的Elastic Compute Cloud使用。


• Greenplum 是一个大型数据仓库DBMS，它实现了MapReduce和SQL。


• XML 根本不是DBMS，它是一种交换格式。但是有些DBMS产品使用XML格式的数据。


• ODBMS 或对象数据库，用于管理复杂数据。似乎没有任何主流的ODBMS产品在主流，也许是因为缺乏标准化。标准SQL正在逐渐获得一些OO功能（例如可扩展的数据类型和表格）。


• Drizzle 是一个关系数据库，它从MySQL中绘制了大量的代码。它包括旨在管理可扩展的云计算系统架构中的数据的各种架构更改。据推测，它将继续使用标准SQL和一些MySQL增强功能。


• Cassandra 是一个高度可扩展的，最终一致的，分布式的，结构化的键值存储，由Amazon Dynamo的作者之一在Facebook上开发，并为Apache项目做出贡献。


• Project Voldemort 是一个非关系的分布式键值存储系统。


• Berkeley DB 也值得一提。它不是下一代，因为它可追溯到20世纪90年代初。它是一个流行的键值存储，很容易嵌入到各种应用程序。

• CouchDB is a non-relational database. They call it a document-oriented database.
• Amazon SimpleDB is also a non-relational database accessed in a distributed manner through a web service. Amazon also has a distributed key-value store called Dynamo, which powers some of its S3 services.
• Dynomite and Kai are open source solutions inspired by Amazon Dynamo.
• BigTable is a proprietary data storage solution used by Google, and implemented using their Google File System technology. Google's MapReduce framework uses BigTable.
• Hadoop is an open-source technology inspired by Google's MapReduce, and serving a similar need, to distribute the work of very large scale data stores.
• Scalaris is a distributed transactional key/value store. Also not relational, and does not use SQL. It's a research project from the Zuse Institute in Berlin, Germany.
• RDF is a standard for storing semantic data, in which data and metadata are interchangeable. It has its own query language SPARQL, which resembles SQL superficially, but is actually totally different.
• Vertica is a highly scalable column-oriented analytic database designed for distributed (grid) architecture. It does claim to be relational and SQL-compliant. It can be used through Amazon's Elastic Compute Cloud.
• Greenplum is a high-scale data warehousing DBMS, which implements both MapReduce and SQL.
• XML isn't a DBMS at all, it's an interchange format. But some DBMS products work with data in XML format.
• ODBMS, or Object Databases, are for managing complex data. There don't seem to be any dominant ODBMS products in the mainstream, perhaps because of lack of standardization. Standard SQL is gradually gaining some OO features (e.g. extensible data types and tables).
• Drizzle is a relational database, drawing a lot of its code from MySQL. It includes various architectural changes designed to manage data in a scalable "cloud computing" system architecture. Presumably it will continue to use standard SQL with some MySQL enhancements.
• Cassandra is a highly scalable, eventually consistent, distributed, structured key-value store, developed at Facebook by one of the authors of Amazon Dynamo, and contributed to the Apache project.
• Project Voldemort is a non-relational, distributed, key-value storage system. It is used at LinkedIn.com
• Berkeley DB deserves some mention too. It's not "next-gen" because it dates back to the early 1990's. It's a popular key-value store that is easy to embed in a variety of applications. The technology is currently owned by Oracle Corp.

另请参阅Richard Jones的这篇好文章： Anti-RDBMS：分布式键值存储列表 。他更详细地描述了一些这些技术。

Also see this nice article by Richard Jones: "Anti-RDBMS: A list of distributed key-value stores." He goes into more detail describing some of these technologies.

关系数据库有弱点，可以肯定。人们一直在争论说，自从第一次引入之日起，他们并不处理所有的数据建模需求。

Relational databases have weaknesses, to be sure. People have been arguing that they don't handle all data modeling requirements since the day it was first introduced.

年复一年，研究人员提出了管理数据的新方法来满足特殊要求：处理不适合关系模型的数据关系的要求， else要求大规模量或速度的数据处理需要在服务器的分布式集合而不是中央数据库服务器上进行。

Year after year, researchers come up with new ways of managing data to satisfy special requirements: either requirements to handle data relationships that don't fit into the relational model, or else requirements of high-scale volume or speed that demand data processing be done on distributed collections of servers, instead of central database servers.

即使这些先进技术做得很好解决他们设计的专门的问题，关系数据库仍然是一个很好的通用解决方案为大多数业务需求。 SQL不会消失。

Even though these advanced technologies do great things to solve the specialized problem they were designed for, relational databases are still a good general-purpose solution for most business needs. SQL isn't going away.

我在php | Architect杂志上写了一篇文章，关系数据库和关系数据库与非关系数据库中的数据建模。 http://www.phparch.com/magazine/2010-2/september/

I've written an article in php|Architect magazine about the innovation of non-relational databases, and data modeling in relational vs. non-relational databases. http://www.phparch.com/magazine/2010-2/september/

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