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This article mainly introduces what is the difference between data warehouse and database, which has certain reference value. Interested friends can refer to it. I hope you will gain a lot after reading this article.

The database is designed for transaction, and the data warehouse is designed for topic. Databases generally store online transaction data, while data warehouses generally store historical data.

Database design is to avoid redundancy as far as possible, generally use the rules in line with the normal form to design, data warehouse design is to deliberately introduce redundancy, using anti-normal form to design.

The database is designed to capture data, the data warehouse is designed to analyze data, and its two basic elements are dimension table and fact table. (dimension is the point of view of the problem, such as time, department, dimension table is the definition of these things, fact table contains the data to be queried, at the same time dimensional ID)

Data warehouse is produced in order to further mine data resources and make decisions when a large number of databases already exist. It is by no means a so-called "large database". So what is the difference between a data warehouse and a traditional database? Let's first look at W.H.Inmon 's definition of a data warehouse: a topic-oriented, integrated, time-dependent, and immutable collection of data.

"topic-oriented": traditional databases mainly process data for applications and may not store data according to the same topic; data warehouses focus on data analysis and are stored according to topics. This is similar to the difference between a traditional farmer's market and a supermarket-in the market, cabbage, radish and coriander will be on a stall, if they are sold by a small seller, while in the supermarket, cabbage, radish and coriander will each have one piece. In other words, the food (data) in the market is stacked (stored) according to the vendor (application), while in the supermarket it is stacked according to the type of dish (the same theme).

"time-related": when the database stores information, it does not emphasize that there must be time information. Data warehouse is different, for the need of decision-making, the data in the data warehouse should indicate the time attribute. Time attribute is very important in decision-making. They are also customers who have bought nine cars in the past three months, and the other has never bought them in the last year, which means different things to policy makers.

"unmodifiable": the data in the data warehouse is not up to date, but comes from other data sources. Data warehouse reflects historical information and is not the kind of daily transaction data that many databases deal with (some databases such as telecom billing database or even real-time information). As a result, the data in the data warehouse is rarely or not modified at all; of course, adding data to the data warehouse is allowed.

The emergence of data warehouse is not to replace the database. At present, most data warehouses are managed by relational database management systems. It can be said that databases and data warehouses complement each other and have their own advantages.

Generally speaking, the main differences between data warehouse and database are:

The main contents are as follows: (1) the database is transaction-oriented and the data warehouse is topic-oriented.

(2) the database generally stores online transaction data, and the data warehouse generally stores historical data.

(3) the database design is to avoid redundancy as far as possible, and the data warehouse is designed to introduce redundancy intentionally.

(4) the database is designed to capture data, and the data warehouse is designed to analyze data.

Thank you for reading this article carefully. I hope the article "what is the difference between data warehouse and database" shared by the editor will be helpful to everyone. At the same time, I also hope that you will support and pay attention to the industry information channel. More related knowledge is waiting for you to learn!

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