Microsoft SQL Server
This page was last modified on 28 June 2016, at 09:41.
|Written in||C,C++, C#|
|Operating system||Unix, Windows, OS/2|
Microsoft SQL Server - management system relational database (RDBMS) developed by Microsoft. It is written in C, C ++, C #. Using Transact-SQL language, which is the implementation of the ANSI / ISO standard Structured Query Language (SQL) extensions.
|1.0 (OS/2)||1989||SQL Server 1.0 (16 bit)||Ashton-Tate / MS SQL Server|
|1.1 (OS/2)||1991||SQL Server 1.1 (16 bit)||-|
|4.21 (WinNT)||1993||SQL Server 4.21||SQLNT|
|6.0||1995||SQL Server 6.0||SQL95|
|6.5||1996||SQL Server 6.5||Hydra|
|7.0||1998||SQL Server 7.0||Sphinx|
|-||1999||SQL Server 7.0 OLAP Tools||Palato mania|
|8.0||2000||SQL Server 2000||Shiloh|
|8.0||2003||SQL Server 2000 64-bit||Liberty|
|9.0||2005||SQL Server 2005||Yukon|
|10.0||2008||SQL Server 2008||Katmai|
|10.25||2010||Azure SQL DB||Cloud Database or CloudDB|
|10.50||2010||SQL Server 2008 R2||Kilimanjaro (aka KJ)|
|11.0||2012||SQL Server 2012||Denali|
|12.0||2014||SQL Server In-Memory OLTP||Hekaton|
|14||2016||SQL Server 2016|
The Database Engine is the core service for storing, processing and securing data. The Database Engine provides controlled access and rapid transaction processing to meet the requirements of the most demanding data consuming applications within your enterprise. The Database Engine also provides rich support for sustaining high availability.
Data Quality Services
SQL Server Data Quality Services (DQS) provides you with a knowledge-driven data cleansing solution. DQS enables you to build a knowledge base, and then use that knowledge base to perform data correction and deduplication on your data, using both computer-assisted and interactive means. You can use cloud-based reference data services, and you can build a data management solution that integrates DQS with SQL Server Integration Services and Master Data Services.
Analysis Services is an analytical data platform and toolset for personal, team, and corporate business intelligence. Servers and client designers support traditional OLAP solutions, new tabular modeling solutions, as well as self-service analytics and collaboration using PowerPivot, Excel, and a SharePoint Server environment Analysis Services also includes Data Mining so that you can uncover the patterns and relationships hidden inside large volumes of data.
Integration Services is a platform for building high performance data integration solutions, including packages that provide extract, transform, and load (ETL) processing for data warehousing.
Master Data Services
Master Data Services is the SQL Server solution for master data management. A solution built on Master Data Services helps ensure that reporting and analysis is based on the right information. Using Master Data Services, you create a central repository for your master data and maintain an auditable, securable record of that data as it changes over time.
Replication is a set of technologies for copying and distributing data and database objects from one database to another, and then synchronizing between databases to maintain consistency. By using replication, you can distribute data to different locations and to remote or mobile users by means of local and wide area networks, dial-up connections, wireless connections, and the Internet.
Reporting Services delivers enterprise, Web-enabled reporting functionality so you can create reports that draw content from a variety of data sources, publish reports in various formats, and centrally manage security and subscriptions.
A data storehouse is a database, which is a collection of tables with typed columns. SQL Server supports different types of data, including primary types such as Integer, Float, Decimal, Shar (including character strings), Varchar (string variable characters), binary (for unstructured data clots), the Text (for text data) and others.
Server statistics is available as virtual tables and views (called Dynamic Management Views or DMVs). In addition to the tables, the database may also contain other objects, including views, stored procedures, indexes and constraints, as well as the transaction log. The SQL Server database can contain a maximum of 231 objects, and can span multiple files at the operating system level, with a maximum size of 260 bytes of the file (1 exabyte). The data in the database are stored in the primary data files with an extension .mdf. Secondary data files that have been identified with the extension .ndf, are used to let the data from a single database be extended to more than one file, and possibly more than one file system. The log files are identified with the .ldf extension.
Disk space is divided into sequentially numbered pages, each 8 KB. Page is the basic input / output unit for SQL Server operations. Page marked 96-byte header which stores metadata about the page, including the page number, page type, free space on the page and the object identifier to which they belong. Page type defines the data contained on the page: the data stored in the database, index, distribution map, which contains information about how pages are allocated tables and indexes, change map that contains information about the changes made to other pages since the last backup copy or logging, or contain large data types, such as image or text.
For physical storage table, its rows are divided into a number of sections (numbered from 1 to N). The partition size is determined by the user; by default, all lines are in the same section. The table is divided into several sections to extend the database of clusters of data. The lines in each section is stored or as a B-tree or heap.
Working with Data
The main way to retrieve data from SQL Server database is a request. The request is expressed using SQL variant called T-SQL. Request declaratively specifies what needs to be obtained. He handled the query processor, which figures out the sequence of steps that will be needed to obtain the required data. The sequence of actions needed to fulfill the request is called the query plan. There may be several ways of processing the same request. For example, a query that contains an operator selection and operator join, first performs join both tables and then a choice, or vice versa. In this case, SQL Server selects plan that is expected faster. This optimization is executed in the request processor.