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zdg收录，使用标签：Amazon, SimpleDB, DataBase，时间：2007-12-16 14:47:40 | 相关网摘，我也收藏
和Amazon S3允许你读写删除文件不一样，通过SimpleDB你可以执行下面的命令：
#CREATE,创建一个新域来放你自己的结构化数据。
#GET,PUT,DELETE你域里的数据。还可以带属性-值对。SimpleDB在你把数据放到域里时自动索引以便能快速被取到，你也不需要预定义模式或者在加入数据时修改模式。每条语句可以带最多256个属性。每个属性值可以是1-1024字节。
#QUERY,用一组运算符查询你的数据：=, !=, <, > <=, >=, STARTS-WITH, AND, OR, NOT, INTERSECTION AND UNION。查询执行时间目前限定在五秒。Amazon SimpleDB为实时应用而设计并为此作优化。
用户只为你用的服务付费。价格方式和Amazon的Simple Storage Service相似，但是有两个主要不同:
-结构化数据存储的费用有数量级的不同。在S3上$0.15每GB月在SimpleDB上变成了$1.50。
-还有一个$0.14每SimpleDB小时的机器使用费。
http://www.yeeyan.com/articles/view/13456/3475
zdg收录，使用标签：Technorati, DataBase，时间：2006-6-30 2:56:12 | 相关网摘，我也收藏
目前处理着大约 10Tb 核心数据, 分布在大约 20 台机器上.通过复制, 多增加了 100Tb 数据, 分布在 200 台机器上. 每天增长的数据 1TB. 通过 SOA 的运用, 物理与逻辑的访问相隔离, 似乎消除了数据库的瓶颈. 值得一提的是, 该扩展过程始终是利用普通的硬件与开源软件来完成的. 毕竟 , Web 2.0 站点都不是烧钱的主. 从数据量来看，这绝对是一个相对比较大的 Web 2.0 应用.Tag 是 Technorati 最为重要的数据元素. 爆炸性的 Tag 增长给 Technorati 带来了不小的挑战.2005 年 1 月的时候, 只有两台数据库服务器, 一主一从. 到了 06 年一月份, 已经是一主一从, 6 台 MyISAM 从数据库用来对付查询, 3 台 MyISAM 用作异步计算.
http://www.dbanotes.net/web/technorati_db_arch.html
zdg收录，使用标签：web2.0, DataBase，时间：2006-6-21 1:47:24 | 相关网摘，我也收藏
I didn't hear that flat files don't scale. What I heard is that some very big sites are saying that traditional databases don't scale, and that the evolution isn't from flat files to SQL databases, but from flat files to sophisticated custom file systems. Brian acknowledges that SQL vendors haven't solved the problem, but doesn't seem to think that anyone else has either.
http://radar.oreilly.com/archives/2006/05/brian_aker_of_mysql_responds.html
zdg收录，使用标签：web2.0, DataBase，时间：2006-6-21 1:44:41 | 相关网摘，我也收藏
Our read-only databases are flat files -- Berkeley DB to be specific -- and are replicated out using our own replication management tools to our webservers. This strategy gives us extremely fast access from the local filesystem. We make thousands of random accesses to this read-only data on each page serve; Berkeley DB offers the performance necessary to be able to still serve our personalized pages rapidly under this load.
http://radar.oreilly.com/archives/2006/05/database_war_stories_8_findory_1.html
zdg收录，使用标签：web2.0, DataBase，时间：2006-6-21 1:42:31 | 相关网摘，我也收藏
Greg Linden of Findory wrote: "I've been enjoying your series on O'Reilly Radar about database war stories at popular startups. I was thinking that it would be fantastic if you could get Jeff Dean or Adam Bosworth at Google to chat a little bit about their database issues. As you probably know, Jeff Dean was involved designing BigTable and the Google File System. Adam Bosworth wrote a much discussed post about the need for better, large scale, distributed databases."
http://radar.oreilly.com/archives/2006/05/database_war_stories_7_google.html
zdg收录，使用标签：web2.0, DataBase，时间：2006-6-21 1:36:17 | 相关网摘，我也收藏
In building our Research data mart, which includes data on book sales trends, job postings), blog postings, and other data sources, Roger Magoulas has had to deal with a lot of very messy textual data, transforming it into something with enough structure to put it into a database. In this entry, he describes some of the problems, solutions, and the skills that are needed for dealing with unstructured data.
http://radar.oreilly.com/archives/2006/05/database_war_stories_6_oreilly.html
zdg收录，使用标签：web2.0, DataBase，时间：2006-6-21 1:32:40 | 相关网摘，我也收藏
Patrick Hogan of NASA World Wind, an open source program that does many of the same things as Google Earth, uses both flat files and SQL databases in his application. Flat files are used for quick response on the client side, while on the server side, SQL databases store both imagery (and soon to come, vector files.) However, he admits that "using file stores, especially when a large number of files are present (millions) has proven to be fairly inconsistent across multiple OS and hardware platforms."
http://radar.oreilly.com/archives/2006/04/database_war_stories_4_nasa_wo.html
zdg收录，使用标签：web2.0, DataBase，时间：2006-6-21 1:29:25 | 相关网摘，我也收藏
Bloglines has several data stores, only a couple of which are managed by "traditional" database tools (which in our case is Sleepycat). User information, including email address, password, and subscription data, is stored in one database. Feed information, including the name of the feed, description of the feed, and the various URLs associated with feed, are stored in another database. The vast majority of data within Bloglines however, the 1.4 billion blog posts we've archived since we went on-line, are stored in a data storage system that we wrote ourselves. This system is based on flat files that are replicated across multiple machines, somewhat like the system outlined in the Google File System paper,but much more specific to just our application. To round things out, we make extensive use of memcached to try to keep as much data in memory as possible to keep performance as snappy as possible.
http://radar.oreilly.com/archives/2006/04/database_war_stories_2_bloglin.html
zdg收录，使用标签：DataBase, SQLServer，时间：2006-6-12 10:14:15 | 相关网摘，我也收藏
SQL Server 2005 is packed with many new features. One of the new features that I would like to discuss in this article is Database Snapshots, which are read only static views of a database. SQL Server 2005 allows you to create multiple snapshots on a database. In this article, I would like to demonstrate the creation of database snapshots and automating the creation of database snapshots.
http://blog.csdn.net/longrujun/archive/2006/06/12/790102.aspx
zdg收录，使用标签：DataBase, SQLServer，时间：2006-6-10 3:07:36 | 相关网摘，我也收藏
Replication is designed to increase data availability by distributing the data across multiple database servers. Availability is increased by allowing applications to scale out the SQL Server read workload across databases. SQL Server 2005 offers enhanced replication using a new peer-to-peer model that provides a new topology in which databases can be synchronized transactionally with any identical peer database.
http://blog.csdn.net/longrujun/archive/2006/06/09/783357.aspx
zdg收录，使用标签：javascript, DataBase，时间：2005-10-31 22:29:41 | 相关网摘，我也收藏
This example illustrates one way of creating a completely JavaScript database with AMASS storage.This was thrown together and just more or less illustrates the possibility of using AMASS storage and TrimPath query javascript in conjunction for an offline in browser database. Why? The possibility of an offline database would be one of the pieces needed to create an offline AJAX application, something very desirable.
http://www.sysbotz.com/articles/jsdb/index.htm
zdg收录，使用标签：DataBase，时间：2005-8-28 1:10:14 | 相关网摘，我也收藏
In this article, I'll summarize 25 of the most useful SQL tuning tips for making SQL statements run faster. Although some of these techniques have been previously described in Oracle manuals and various journals, many others have never been published and are appearing here for the first time.
http://www.dbpd.com/vault/9801xtra.htm
zdg收录，使用标签：DataBase，时间：2005-6-3 18:16:58 | 相关网摘，我也收藏
When looking at SQL performance there's an immediate desire to jump into the queries that the SQL Server is being forced to process and see what can be done to improve them. Unfortunately, it's not always that simple. Sometimes the queries are coming from packaged software that cannot be changed. Other times the queries come from report writing tools and there's just no way to make the queries any better.
http://builder.com.com/5102-6388-5596494.html
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