数据库原理基本概念英文解释

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数据库英语

数据库英语

数据库英语数据库是现代社会中广泛应用的数据管理系统,由于其在各行各业中的重要性,数据库相关的专业术语在英语中也占据着重要的地位。

本文将介绍数据库中常见的英语术语及其解释,以帮助读者更好地理解数据库领域的知识。

数据库基础1.Database:数据库,是指长期储存在计算机中,有组织、永久存储的数据集合。

它通常受到数据库管理系统(DBMS)的管理。

2.Table:表,数据库中的基本组成单位,用来存储特定类型的数据。

表由行和列组成,每行代表一个记录,每列代表一个字段。

3.Record:记录,表中的一行数据,包含了一组相关的数据。

4.Field:字段,表中的一个列,代表一个数据项或属性。

数据库查询1.Query:查询,是指根据特定条件从数据库中检索所需信息的操作。

2.Select:选择,查询语句中的关键字之一,用于选择需要检索的字段。

3.Where:条件,查询语句中的关键字之一,用于指定检索的条件。

4.Join:连接,用于将两个或多个表中相关字段的数据关联起来。

数据库管理1.DBMS:数据库管理系统,是指用来管理数据库的软件系统,负责数据的存储、检索、更新和管理。

2.SQL:结构化查询语言,是一种用于与关系型数据库通信的标准语言。

3.Index:索引,用于提高数据库查询效率的数据结构,通常基于一个或多个字段创建索引。

4.Backup:备份,是指对数据库中的数据进行定期复制和存档,以防止数据丢失。

数据库安全1.Security:安全性,数据库安全性是指保护数据库不受未经授权的访问、破坏和泄露的措施。

er:用户,数据库中被授权访问和操作数据库的个体或实体。

3.Permission:权限,用来控制用户对数据库对象的访问和操作权限的设置。

4.Encryption:加密,是指对数据库中的敏感数据进行转换,以保护数据的安全性。

数据库发展趋势1.Big Data:大数据,指的是规模巨大、种类繁多的数据集合,对传统数据库系统的处理能力提出了挑战。

数据库原理基本概念英文解释

数据库原理基本概念英文解释

数据库原理基本概念英文解释Database principles refer to the fundamental concepts that define the structure, functionality, and management of adatabase system. These principles are essential for designing, implementing, and maintaining a reliable and efficient database. In this essay, I will discuss the basic concepts and principlesof databases in detail, including data modeling, data integrity, normalization, indexing, and database transactions.Data Modeling:Data modeling is the process of defining the structure and relationships of the data in a database. It involves identifying and organizing the various entities, attributes, andrelationships that exist within the domain of an application. There are different types of data models, such as the conceptual, logical, and physical data models. The conceptual data model describes the high-level view of the data, the logical datamodel represents the data structure using entities, attributes, and relationships, and the physical data model maps the logical data model to a specific database management system.Data Integrity:Data integrity ensures the accuracy, consistency, and reliability of data stored in a database. It ensures that the data values conform to defined rules or constraints. There arefour types of data integrity: entity integrity, referential integrity, domain integrity, and user-defined integrity. Entity integrity ensures that each row in a table has a unique identifier. Referential integrity ensures that relationships between tables are maintained. Domain integrity ensures that data values are within certain predefined ranges. User-defined integrity ensures that additional business rules or constraints are enforced.Normalization:Normalization is the process of organizing data in a database to reduce redundancy and improve data integrity. It involves breaking down larger tables into smaller, more manageable entities and establishing relationships between them. The normalization process follows a series of normal forms, such as First Normal Form (1NF), Second Normal Form (2NF), Third Normal Form (3NF), etc. Each normal form has a set of rules that need to be satisfied to ensure data integrity and eliminate data anomalies, such as update, insertion, and deletion anomalies.Indexing:Indexing is a technique used to improve the efficiency of data retrieval operations in a database. It involves creating an index on one or more columns of a table, which allows the database system to locate specific rows quickly using the indexed column(s). Indexes are typically implemented as B-treesand provide a faster search mechanism by reducing the number of disk I/O operations required to locate data. Indexes should be carefully designed and maintained to balance the trade-off between query performance and the overhead of maintaining the index.Database Transactions:。

数据库原理与应用英语

数据库原理与应用英语

数据库原理与应用英语Database Principles and ApplicationsIntroduction:Database Principles:1. Data Organization: A database is a structured collection of data that is organized and stored in a systematic manner. The organization of data is achieved through the use of tables, which consist of rows and columns. Each row in a table represents a record, while each column represents a specific attribute or characteristic of that record.2. Data Independence: One of the key principles of database systems is data independence. This means that the physical organization of data is separate from the logical structure, allowing for easier management and modification of data. Changes to the physical structure, such as storage media or access methods, do not affect the logical structure or the way data is represented to users.3. Data Integrity: Data integrity refers to the accuracy and consistency of data. It is crucial to ensure that databases contain valid and reliable information. Various mechanisms, such as constraints, triggers, and referential integrity, are used to enforce data integrity by preventing the entry of incorrect or inconsistent data.4. Data Security: Data security is another important principle of database systems. It involves protecting sensitive and confidential information from unauthorized access, use, disclosure, or modification. Security measures, such as encryption, access control, and audit trails, are implemented to safeguard the data stored in databases.Database Applications:1. Business Management: Databases play a vital role in managing business operations. They are used to store and handle various types of business data, such as customer information, inventory details, sales records, and financial data. By efficiently storing and retrieving data, businesses can make informed decisions, improve efficiency, and streamline their operations.4. Healthcare: Databases are critical for managing patient records, medical histories, and other healthcare-related information. Electronic Health Record (EHR) systems storepatient data and facilitate its secure sharing among healthcare providers. Databases also support medical research, drug discovery, and clinical trials by providing a structured repository of medical information.Conclusion:。

数据库原理 英文课件Chapter3- The Relational Data Model

数据库原理 英文课件Chapter3- The Relational Data Model
3
The things you should know…
The basic principle of relational database is proposed by E.F.Codd in 1970. The first RDBMS production is System R The most popular RDBMS
5
Attributes (属性)
Attributes of a relation serve us as names for the columns of the relation. Usually, the attributes describes the meaning of entries in the column below.
11
An Example of Relation Instance
Relation: Person (Name, Address, Telephone)
Relation Instance:
Name
Address
Telephone
Bob
123 Main St
555-1234
Bob
128 Main St
Example: Movies (title, year, length, fileType)
Database schema = a set of all relation schemas
Movies(Title, Year, Length, FileType) Star(Name, Age) Studio(StudioName, Addr)
6
Schemas(模式)
The name of a relation and the set of attributes for a relation is called the schema for that relation. We show the schema for the relation with the relation name followed by a parenthesized list of its attributes.

unit1:数据库原理、sql(ddl、dml)

unit1:数据库原理、sql(ddl、dml)

结构化查询语言SQL(Structured Query Language)是结构化查询语言的缩写。

SQL是在关系数据库上执行数据操作、检索及维护所使用的标准语言,可以用来查询数据,操作数据、定义数据、控制数据,所有数据库都使用相同或者相似的语言。

SQL可分为:1.数据定义语言(DDL):Data Definition Language用于建立、修改、删除数据库对象,包括创建语句(create)、修改语句(alter)、删除语句(drop),比如使用 create table创建表,使用alter table修改表,使用drop table删除表等动作。

这类语言不需要事务的参与,自动提交。

2.数据操作语言(DML):Data Manipulation Language用于改变数据库,包括insert、update、delete三条语句,分别用于对数据库数据的插入、更新、删除。

DML语言和事务是相关的,执行完DML操作后必须经过事务控制语句提交后才能真正的将改变引用到数据库中。

3.事务控制语言(TCL):Transaction Control Language用来维护数据一致性的语句,包括提交commit、回滚rollback,保存点savepoint三条语句,其中commit用来确认已经进行的数据库改变, rollback语句用来取消已经进行的数据库改变,当执行DML操作后(也就是上面说的增加、修改、删除等动作),可以使用commit语句来确认这种改变,或者使用rollback取消这种改变。

savepoint语句用来设置保存点,使当前的事务可以回退到指定的保存点,便于取消部分改变。

4.数据查询语言(DQL):Data Query Language用来查询所需要的数据,例如select。

5.数据控制语言(DCL):Data Control Language用于执行权限的授予和收回操作、创建用户等,包括授予grant语句、收回revoke语句、create user语句,其中grant用于给用户或角色授予权限,revoke 用于回收用户或角色已有的权限。

数据库 专业英语翻译

数据库 专业英语翻译

数据库数据库(Database)是按照数据结构来组织、存储和管理数据的仓库,它产生于距今五十年前,随着信息技术和市场的发展,特别是二十世纪九十年代以后,数据管理不再仅仅是存储和管理数据,而转变成用户所需要的各种数据管理的方式。

数据库有很多种类型,从最简单的存储有各种数据的表格到能够进行海量数据存储的大型数据库系统都在各个方面得到了广泛的应用.一.数据管理的诞生数据库的历史可以追溯到五十年前,那时的数据管理非常简单。

通过大量的分类、比较和表格绘制的机器运行数百万穿孔卡片来进行数据的处理,其运行结果在纸上打印出来或者制成新的穿孔卡片.而数据管理就是对所有这些穿孔卡片进行物理的储存和处理。

然而,1 9 5 1 年雷明顿兰德公司(Remington Rand Inc.)的一种叫做Univac I 的计算机推出了一种一秒钟可以输入数百条记录的磁带驱动器,从而引发了数据管理的革命。

1956 年IBM生产出第一个磁盘驱动器—- the Model 305 RAMAC.此驱动器有50 个盘片,每个盘片直径是2 英尺,可以储存5MB的数据。

使用磁盘最大的好处是可以随机地存取数据,而穿孔卡片和磁带只能顺序存取数据。

数据库系统的萌芽出现于60 年代。

当时计算机开始广泛地应用于数据管理,对数据的共享提出了越来越高的要求。

传统的文件系统已经不能满足人们的需要。

能够统一管理和共享数据的数据库管理系统(DBMS)应运而生。

数据模型是数据库系统的核心和基础,各种DBMS 软件都是基于某种数据模型的。

所以通常也按照数据模型的特点将传统数据库系统分成网状数据库、层次数据库和关系数据库三类。

二.结构化查询语言(SQL)1974 年,IBM的Ray Boyce和Don Chamberlin将Codd关系数据库的12条准则的数学定义以简单的关键字语法表现出来,里程碑式地提出了SQL (Structured Query Language)语言。

数据库原理与应用主要术语和概念

数据库原理与应用主要术语和概念

数据(Data):描述事物的符号记录。

数据库(DataBase,DB)长期储存在计算机内的、有组织的、可共享的数据集合。

数据库中的数据按一定的数据模型组织、描述和储存,具有较小的冗余度、较高的数据独立性和易扩展性,并可为各种用户共享。

数据库管理系统(DataBase Management System,DBMS)位于用户与操作系统之间的一层数据管理软件。

主要功能包括以下几个方面:1.数据定义功能:数据定义语言(Data Definition Language,DDL)2.数据操纵功能: 数据操纵语言(Data Manipulation Language,DML)3.数据库的运行管理:4.数据库的建立和维护功能:数据库系统(DataBase System,DBS)指在计算机系统中引入数据库后的系统,一般由数据库、数据库管理系统(及其开发工具)、应用系统、数据库管理员和用户构成。

数据库管理员(DataBase Administrator,DBA)数据库的定义:一个按照一定数据结构来组织,存储,管理的数据集合数据库的特点:数据结构化:实现数据共享:避免了数据的不一致性有利于数据的安全性有利于保证数据的完可以发现故障和恢复正常状态数据库特(优点)点:采用特定的数据模型,使数据结构化;数据的独立性高;数据的共享性好,数据冗余度低;为用户提供了方便的用户接口;统一的数据控制等数据管理系统的定义:对数据库进行管理的软件系统,它负责数据库中的数据组织,数据操纵,数据维护,数据控制及保护和数据服务等DBMS的功能:数据定义:数据操纵:数据控制:数据组织与存取:数据库建立与维护:运行管理:数据库系统:一个带有数据库的计算机应用系统,它由支持该系统开发,使用与运行维护的硬件,软件和人员组成数据库应用系统:DBAS是一个使用数据库的计算机应用系统,它是包括应用程序,数据,数据库以及与该系统的开发,维护和使用有关的文档的完整集合。

数据库专业英语

数据库专业英语

数据库专业英语文章摘要:数据库专业英语是指与数据库相关的专业术语和表达方式,它涉及到数据库的基本概念、结构、设计、操作、管理、应用等方面。

掌握数据库专业英语对于学习和使用数据库技术是非常有益的,可以提高沟通和理解的效率,也可以拓展知识和视野。

本文将介绍一些常用的数据库专业英语,包括数据模型、数据操作、数据分析、数据安全等,并给出中英文对照的表格,以便于读者参考和学习。

1. 数据模型数据模型(Data Model)是对现实世界特征的数字化的模拟和抽象,它描述了数据的结构、属性、联系和约束。

不同的数据模型有不同的特点和适用范围,常见的数据模型有层次模型(Hierarchical Model)、网状模型(Network Model)、关系模型(Relational Model)、对象模型(Object Model)等。

下表列出了一些与数据模型相关的专业英语:中文英文数据Data数据库Database数据库管理系统Database Management System (DBMS)数据字典Data Dictionary数据仓库Data Warehouse数据湖Data Lake实体Entity属性Attribute域Domain关系Relation元组Tuple主键Primary Key外键Foreign Key视图View索引Index约束Constraint2. 数据操作数据操作(Data Manipulation)是指对数据库中的数据进行增加、删除、修改和查询等操作,通常使用一种称为结构化查询语言(Structured Query Language,简称SQL)的标准语言。

SQL语言分为数据定义语言(Data Definition Language,简称DDL)、数据操纵语言(Data Manipulation Language,简称DML)、数据控制语言(Data Control Language,简称DCL)等部分。

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数据库原理基本概念Basic concepts of database theory一、数据---DataData is everything.Data can exist in a variety of forms -- as digital numbers, text, image, sound, video and etc.二、数据库---DatabaseA database is a repository for a collection of computerized data files.A database is an organized collection of data for one or more purposes, usually in digital form. The data are typically organized to model relevant aspects of reality (for example, the availability of rooms in hotels), in a way that supports processes requiring this information (for example, finding a hotel with vacancies). The term "database" refers both to the way its users view it, and to the logical and physical materialization of its data, content, in files, computer memory, and computer data storage.三、数据库系统---DBS(Database System)A database system is a term that is typically used to encapsulate the constructs of a data model, database Management system (DBMS) and database.四、数据库管理系统---DBMS(Database ManagementSystem)A database management system (DBMS) is a software package with computer programs that control the creation, maintenance, and the use of a database. It allows organizations to conveniently develop databases for various applications by database administrators (DBAs) and other specialists.A collection of programs that enables you to store, modify, and extract information from a database.五、数据库管理员---DBA(Database Administrator)A database administrator is a person responsible for the design, implementation, maintenance and repair of an organization's database.六、模式---SchemaA database schema of a database system is its structure described in a formal language supported by the database management system (DBMS) and refers to the organization of data to create a blueprint of how a database will be constructed.In other words, schema is the structure of the database that defines the objects in the database.七、内模式---Internal SchemaInternal Schema: storage schema– Describes how data is stored and what the physical structureof data is.– Totally dependent on particular implementation.– There is only one internal schema in a DB.八、外模式---External SchemaExternal Schema: user schema or subschema– Interface between users and DBS– Describes the logical structure of some local data oriented tosome applications and users– There may be many external schemata in a DB.九、三级模式---Three Levels of Schema-Physical level: describes how a record (e.g., customer) is stored.-Logical level: describes data stored in database, and therelationships among the data.-View level: application programs hide details of data types. Views can also hide information (such as an e mployee’s salary)for security purposes.十、映像---MappingData mapping is the process of creating data element mappings between two distinct data models. Data mapping is used as a first step for a wide variety of data integration tasks including:●Data transformation or data mediation between a data source anda destination●Identification of data relationships as part of data lineageanalysis●Discovery of hidden sensitive data such as the last four digitssocial security number hidden in another user id as part of a datamasking or de-identification project●Consolidation of multiple databases into a single data base andidentifying redundant columns of data for consolidation orelimination十一、逻辑独立性---Logical Independence When schema changes (e.g., new relation/new attribute added), DBA changes the Ex-schema/schema mapping, so the external schema can stay unchanged, i.e. applications needn’t be changed.十二、物理独立性---Physical Independence When internal schema changes ,DBA changes the schema/internal schema mapping, so the schema can stay unchanged . Thus, the external schema also keeps the same.十三、数据模型---Data ModelA data model in software engineering is an abstract model, that documents and organizes the business data for communication between team members and is used as a plan for developing applications, specifically how data is stored and accessed.A data model can be sometimes referred to as a data structure, especially in the context of programming languages. Data models are often complemented by function models, especially in the context of enterprise models.。

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