Objectives:
1.Appreciate SQL Server as a database server
2.Identify the SQL Server tools
Instance: 1.Default Instance 2.Named Instance
1.Database Engine:
(1).Service Broker:https://www.cnblogs.com/xwdreamer/archive/2012/06/29/2570389.html
(2)Replication:https://redis.io/topics/replication
(3)Full-text search:https://en.wikipedia.org/wiki/Full-text_search
(4)Notification services:https://msdn.microsoft.com/zh-cn/library/ms170337.aspx
2.Integration(集成) Services:https://docs.microsoft.com/en-us/sql/integration-services/integration-services-ssis-projects-and-solutions
3.Analysis Services:https://docs.microsoft.com/en-us/sql/analysis-services/analysis-services
4.Reporting Services:https://docs.microsoft.com/en-us/sql/reporting-services/create-deploy-and-manage-mobile-and-paginated-reports
5.Master Data Services:https://www.cnblogs.com/kevinbi/p/7236935.html
Types of SQL Statements
详见：http://www.jb51.net/article/40359.htm
1.Data Definition Language(DDL):
DDL（data definition language）是数据定义语言：DDL比DML要多，主要的命令有CREATE、ALTER、DROP等，DDL主要是用在定义或改变表（TABLE）的结构，数据类型，表之间的链接和约束等初始化工作上，他们大多在建立表时使用。
2.Data Manipulation Language(DML):
DML（data manipulation language）是数据操纵语言：它们是SELECT、UPDATE、INSERT、DELETE，就象它的名字一样，这4条命令是用来对数据库里的数据进行操作的语言。
3.Data Control Language(DCL):
DCL（DataControlLanguage）是数据库控制语言：是用来设置或更改数据库用户或角色权限的语句，包括（grant,deny,revoke等）语句。
4.Data Query Language(DQL):是数据库查询语言。
关系见下图：（图中DCL中有一处的更改：“Vevoke”变为“Revoke”）
Summary:
1.A business application can have three elements:user interface,business logic ,and data storage.
2.A database server is used to store and manage the database in a business application.
3.SQL Server consists of the five core components :database engine, intergration services, analysis services, reporting services, and master data services.
4.A database engine provides support to store,query ,process,and secure(保护) data on a database server. Integration services allow you to gather(收集) and integrate（集合） this varied (多样的) data in a consistent format in a common database called the data warehouse.(https://en.wikipedia.org/wiki/Data_warehouse)