NoSql 和数据仓库
NoSql 和数据仓库技术/理论之间有什么关系？
他们有哪些共同的概念？
它们之间的基本区别是什么？
您认为双方如何从对方那里获益/丰富？
我认为你的想法应该对这两种技术的未来都有帮助。
更新：
一些有用的链接：
第二次更新：
What are the relations between NoSql and Data-Warehouse technologies/theories?
What concepts they share?
What are the basic differences between them?
How do you think each could be benefits/enriches from the other?
I think your ideas should be helpful for the future of both technologies.
UPDATE:
Some useful links:
2nd UPDATE:
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数据仓库与 NoSQL 几乎没有什么共同点 - 主要相似之处在于任何两个数据仓库都可以有非常不同的理念或约定，就像任何两个 NoSQL 系统可以几乎不相关一样。
它们唯一共同的概念是它们都用于分析大量数据。
NoSQL 解决方案通常管理相对有限的模式，在少数实体中具有较大基数，而数据仓库通常具有大量事实和维度（在维度模型中）或 3NF 模型中的大量实体。 DW 系统通常管理多个业务线并尝试合并这些数据。
DW 系统通常具有 SQL 报告功能，允许您以标准方式访问所有数据。 NoSQL 系统通常更多地基于代码 - 例如 Map/Reduce。
Data Warehouses have very little in common with NoSQL - the main similarity is that any two data warehouses can have very different philosopohies or conventions just like any two NoSQL systems can be nearly unrelated.
The only concept they share is that they are both used to analyze large amounts of data.
NoSQL solutions usually manage relatively limited schemas with large cardinality in few entities, while data warehouses typically have lots of facts and dimensions (in a dimensional model) or lots of entities in a 3NF model. DW systems usually manage multiple lines of business and attempt to combine that data.
DW systems typically have reporting abilities in SQL which allows you to access all the data in a standard way. NoSQL systems are typically more code-based - for instance Map/Reduce.
Ayende Rahien 在他的博客中对此进行了很好的解释：
http://ayende.com/blog/ 4552/nosql-and-data-warehousing
“对于数据仓库，我认为关系/OLAP世界具有显着的优势，主要是因为在很多BI场景中，你希望允许用户探索数据，这就是使用 SQL 工具集很容易，而使用 NoSQL 解决方案则比较困难，但是当您变得太大时（OLAP 场景中的大是非常大的），您可能需要考虑限制用户的选项并采用适合他们需要的 NoSQL 解决方案。 ”。
Ayende Rahien explain it well in his blog:
http://ayende.com/blog/4552/nosql-and-data-warehousing
"For data warehousing, I think that the relational / OLAP world has significant advantages, mostly because in many BI scenarios, you want to allow the users to explore the data, which is easy with the SQL toolset, and harder with NoSQL solutions. But when you get too large (and large in OLAP scenarios is really large), you might want to consider limiting the users’ options and going with a NoSQL solution tailor to what they need."
甲板上我最喜欢的一句话：
“在商业智能案例中，文档数据库远远优于关系数据库。不仅如此，mongoDB 和一些常识让您可以用出色的开源技术取代价值数百万美元的 IBM 级企业解决方案。所有这一切都以快速、敏捷的方式进行。 ”
http://www.10gen.com/presentations/mongodc -2011/time-series-data-storage-mongodb
另外：
“Map/Reduce 可能会成为您的杀手级应用程序，它可以成为解决您所有商业智能疾病的灵丹妙药。这是非常严肃的事情。如果 Google 已经在它身上下了赌注，并将其作为其搜索技术的基础，那么您最好相信这是非常强力的良药。”
http://www.infogain.com/company/perspective-big-data.jsp
My favorite quote from the deck:
"document-databases are far superior to relational databases for business intelligence cases. Not only that, but mongoDB and some common sense lets you replace multimillion dollar IBM-level enterprise solutions with open-source awesomeness. All this in a rapid, agile way."
http://www.10gen.com/presentations/mongodc-2011/time-series-data-storage-mongodb
Also:
"Map/Reduce may yet be your killer app that can be the panacea for all your Business Intelligence ailments. This is very serious stuff. If Google has bet its house on it and has made this the foundation for their search technology, then you better believe that this is very strong medicine."
http://www.infogain.com/company/perspective-big-data.jsp
数据仓库系统通常用于向管理层快速报告，而NoSql系统通常用于处理非常大的数据以进行地图缩减。
数据仓库使用关系数据库，而NoSql使用非关系数据库。
NoSql 数据库比数据仓库更快。
我们在数据仓库中使用SQL，但在NoSql中我们不需要SQL来操作数据。
数据仓库由维度和事实组成，而NoSql由有限的模式组成。
Data warehouse system are generally used for quick reporting to management and NoSql system are generally for handle very large data for map reduction
Data warehouse uses relational database while NoSql use non relational database.
NoSql database are faster than data warehouse.
We use SQL in data warehouse but we need not require SQL for manipulating data in NoSql
Data warehouse consists of dimension and fact while NoSql are consist limited schema.