blocks|key|1178445|text|最简单的解释方法是，数据仓库不仅仅由一个数据库组成。数据库是以某种方式组织的数据集合，但数据仓库是专门为了“促进报告和分析”而组织的。然而，这并不是整个故事的全部，因为数据仓库还包含“检索和分析数据、提取、转换和加载数据以及管理数据字典的方法，也被认为是数据仓库系统的基本组件”。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1178446|Data+Warehouse|offset|length|1178447|entityMap|0|LINK|mutability|MUTABLE|url|http://en.wikipedia.org/wiki/Data_warehouse^0|0|0|E|0|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|O|8|@]|9|@$D|P|E|Q|1|R]]|A|$]]|$1|F|3|-4|5|6|7|S|8|@]|9|@]|A|$]]]|G|$H|$5|I|J|K|A|$L|M]]]]

The simplest way to explain it would be to say that a data warehouse consists of more than just a database. A database is an collection of data organized in some way, but a data warehouse is organized specifically to "facilitate reporting and analysis". This however is not the entire story as data warehousing also contains "the means to retrieve and analyze data, to extract, transform and load data, and to manage the data dictionary are also considered essential components of a data warehousing system".

<a href="http://en.wikipedia.org/wiki/Data_warehouse" rel="noreferrer">Data Warehouse</a>

blocks|key|1178588|text|数据仓库是一种数据库类型。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1178589|除了人们已经说过的话，数据仓库往往是OLAP，具有针对读取而不是写入进行调整的索引等，并且数据被反规范化/转换为更易于读取和分析的形式。|1178590|有些人说“数据库”等同于OLTP+--这不是真的。OLTP也是一种数据库类型。|1178591|其他类型的“数据库”：文本文件、XML、Excel、CSV...、平面文件:-)|1178592|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|J|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|K|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|L|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|M|8|@]|9|@]|A|$]]|$1|H|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|I|$]]

A data warehouse is a TYPE of database.

In addition to what folks have already said, data warehouses tend to be OLAP, with indexes, etc. tuned for reading, not writing, and the data is de-normalized / transformed into forms that are easier to read &amp; analyze.

Some folks have said "databases" are the same as OLTP -- this isn't true. OLTP, again, is a TYPE of database.

Other types of "databases": Text files, XML, Excel, CSV..., Flat Files :-)

blocks|key|964448|text|从非技术角度看:数据库被限制为特定的应用程序或应用程序集。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|964449|数据仓库是一个企业级数据存储库。它将包含来自所有/许多业务部门的数据。它将分享这些信息，以提供业务的全球图景。它对于不同业务部门之间的集成也是至关重要的。|964450|从技术角度看：“数据仓库”这个词还没有给出公认的定义。就个人而言，我将数据仓库定义为数据集市的集合。其中每个数据集市由一个或多个数据库组成，其中数据库特定于特定的问题集(应用程序、数据集或进程)。|964451|简单地说，数据库是数据仓库的一个组件。有很多地方可以探索这个概念，但是因为没有“定义”，你会发现你给出的任何答案都会带来挑战。|964452|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|J|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|K|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|L|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|M|8|@]|9|@]|A|$]]|$1|H|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|I|$]]

From a Non-Technical View:
A database is constrained to a particular applications or set of applications.

A data warehouse is an enterprise level data repository. It's going to contain data from all/many segments of the business. It's going to share this information to provide a global picture of the business. It is also critical to integration between the different segments of the business.

From a Technical view:
The word "Data Warehouse" has been given no recognized definition. Personally, I define a data warehouse as a collection of data-marts. Where each data-mart consists of one or more databases where the database is specific to a specific problem set (application, data-set or process).

Simply put a database is a component of a data-warehouse. There are many places to explore this concept, but because there is no "definition", you will find challenges with any answer you give.

blocks|key|1178769|text|简单地看:+Dataware+->+Huge+using+for+Analytical/storage/+copy+and+Analysis。数据库-->使用常用数据的CRUD操作。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1178770|数据仓库是一种你不经常使用的仓库，而数据库是你经常使用的东西。|1178771|例如：如果我们询问银行对帐单，那么它会给我们过去3/4/6/更多个月的时间，因为它在数据库中。如果你想要更多，它存储在数据屋。|1178772|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|H|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|I|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|J|8|@]|9|@]|A|$]]|$1|F|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|G|$]]

See in simple words : 
Dataware --> Huge data using for Analytical/storage/ copy and Analysis .
Database --> CRUD operation with Frequently used data .

Dataware house is Kind of storage which u are not using on daily basis &amp; Database is something which your dealing frequently .

Eg. If we are asking statement of bank then it gives us for last 3/4/6/more months bcoz it is in database. If you want more than that it stores on Dataware house.

blocks|key|1178818|text|例如:一所房子的价值是$100,000，而且它每年以$1000升值。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|1178819|为了跟踪当前的房价，您将使用数据库，因为该值每年都会更改。|1178820|三年后，你将能够看到房子的价值，也就是$103,000.|1178821|为了跟踪历史房屋价值，您可以使用数据仓库，因为房屋的价值应该是|1178822|$100,000+on+year+0,+
$101,000+on+year+1,+
$102,000+on+year+2,+
$103,000+on+year+3.+|code-block|syntax|javascript|1178823|entityMap^0|B|8|Q|5|0|0|J|9|0|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@$9|T|A|U|B|C]|$9|V|A|W|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|X|8|@]|D|@]|E|$]]|$1|H|3|I|5|6|7|Y|8|@$9|Z|A|10|B|C]]|D|@]|E|$]]|$1|J|3|K|5|6|7|11|8|@]|D|@]|E|$]]|$1|L|3|M|5|N|7|12|8|@]|D|@]|E|$O|P]]|$1|Q|3|-4|5|6|7|13|8|@]|D|@]|E|$]]]|R|$]]

Example: A house is worth <code>$100,000</code>, and it is appreciating at <code>$1000</code> per year. 

To keep track of the current house value, you would use a database as the value would change every year. 

Three years later, you would be able to see the value of the house which is <code>$103,000.</code> 

To keep track of the historical house value, you would use a data warehouse as the value of the house should be 

<pre><code>$100,000 on year 0, 
$101,000 on year 1, 
$102,000 on year 2, 
$103,000 on year 3. 
</code></pre>

blocks|key|1178863|text|任何应用程序的数据存储通常都使用数据库。它可以是关系数据库，也可以是当前流行的非sql数据库。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1178864|数据仓库也是数据库。我们可以调用数据仓库数据库作为专门的数据存储，用于公司的分析报告目的。此数据用于关键业务决策。|1178865|有组织的数据有助于有效地报告和做出业务决策。|1178866|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|H|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|I|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|J|8|@]|9|@]|A|$]]|$1|F|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|G|$]]

Any data storage for application generally uses the database. It could be relational database or no sql databases which are currently trending. 

Data warehouse is also database. We can call data warehouse database as specialized data storage for the analytical reporting purposes for the company. 
This data used for key business decision. 

The organized data helps is reporting and taking business decision effectively.

blocks|key|1178935|text|数据仓库的源可以是数据库集群，因为数据库用于联机事务处理，如在数据仓库中保留当前的records..but，它存储用于联机分析处理的历史数据。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1178936|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

Source for the Data warehouse can be cluster of Databases, because databases are used for Online Transaction process like keeping the current records..but in Data warehouse it stores historical data which are for Online analytical process.

blocks|key|964771|text|数据仓库是通常存放在数据库上的一种数据结构。数据仓库指的是数据模型和存储在其中的数据类型-为分析目的而建模的数据(数据模型)。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|964772|数据库可以归类为容纳数据的任何结构。传统上，这是一个关系型数据库管理系统，如Oracle、SQL+Server或MySQL。然而，数据库也可以是像Apache+Cassandra这样的NoSQL数据库，或者像亚马逊网络服务RedShift这样的柱状MPP。|964773|您可以看到，数据库只是一个存储数据的地方；数据仓库是一种存储数据的特定方式，它服务于特定的目的，即服务于分析查询。|964774|OLTP与OLAP不会告诉您DW和数据库之间的区别，OLTP和OLAP都驻留在数据库中。它们只是以不同的方式存储数据(不同的数据模型方法)并服务于不同的目的(OLTP+-记录事务，针对更新进行了优化；OLAP+-分析信息，针对读取进行了优化)。|964775|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|J|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|K|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|L|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|M|8|@]|9|@]|A|$]]|$1|H|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|I|$]]

A Data Warehouse is a type of Data Structure usually housed on a Database. The Data Warehouse refers the the data model and what type of data is stored there - data that is modeled (data model) to server an analytical purpose.

A Database can be classified as any structure that houses data. Traditionally that would be an RDBMS like Oracle, SQL Server, or MySQL. However a Database can also be a NoSQL Database like Apache Cassandra, or an columnar MPP like AWS RedShift. 

You see a database is simply a place to store data; a data warehouse is a specific way to store data and serves a specific purpose, which is to serve analytical queries. 

OLTP vs OLAP does not tell you the difference between a DW and a Database, both OLTP and OLAP reside on databases. They just store data in a different fashion (different data model methodologies) and serve different purposes (OLTP - record transactions, optimized for updates; OLAP - analyze information, optimized for reads).

blocks|key|1179062|text|数据仓库(DW)是从不同来源收集和管理数据以提供有意义的业务洞察的过程。数据仓库通常用于连接和分析来自不同来源的业务数据。数据仓库是BI系统的核心，用于数据分析和报表。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1179063|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

A Data Warehousing (DW) is process for collecting and managing data from varied sources to provide meaningful business insights. A Data warehouse is typically used to connect and analyze business data from heterogeneous sources. The data warehouse is the core of the BI system which is built for data analysis and reporting.

What is the difference between a database and a data warehouse?

Aren't they the same thing, or at least written in the same thing (ie. Oracle RDBMS)?

What is the difference between a database and a data warehouse?

数据库管理系统

关系型数据库

数据库管理

数据库集群

数据存储

数据集市

SQL数据库

数据结构

数据仓库

数据分析

SQL Server

Cassandra

数据库

NoSQL

MySQL

OLAP

OLTP

数据库和数据仓库之间的区别是什么？它们不是相同的东西吗，或者至少是写在相同的东西上的(即，Oracle RDBMS)？

问数据库和数据仓库之间的区别是什么？
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