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• Date and Time: Four new date and time data types have been added, making working with
time much easier than it ever has in the past. They include: DATE, TIME, DATETIME2, and
DATETIMEOFFSET.

• Spatial: Two new spatial data types have been added--GEOMETRY and GEOGRAPHY--
which you can use to natively store and manipulate location-based information, such as Global
Positioning System (GPS) data.

• HIERARCHYID: The HIERARCHYID data type is used to enable database applications to
model hierarchical tree structures, such as the organization chart of a business.

• FILESTREAM: FILESTREAM is not a data type as such, but is a variation of the
VARBINARY(MAX) data type that allows unstructured data to be stored in the file system
instead of inside the SQL Server database. Because this option requires a lot of involvement
from both the DBA administration and development side, I will spend more time on this topic
than the rest.

Date and Time

In SQL Server 2005 and earlier, SQL Server only offered two date and time data types: DATETIME
and SMALLDATETIME. While they were useful in many cases, they had a lot of limitations,
including:

To overcome these problems, SQL Server 2008 introduces four new date and time data types, described in the following sections. All of these new date and time data types work with SQL Server 2008 date and time functions, which have been enhanced in order to properly understand the new In addition, some new date and time functions have been added to take advantage of the capabilities of these new data types. The new functions include SYSDATETIME, TODATETIMEOFFSET, SYSUTCDATETIME, and DATE.

As you can imagine, the DATE data type only stores a date in the format of YYYY-MM-DD. It has
a range of 0001-01-01 through 9999-12-32, which should be adequate for most business and
scientific applications. The accuracy is 1 day, and it only takes 3 bytes to store the date.

--Sample DATE output
DECLARE @datevariable as DATE
SET @datevariable = getdate()
PRINT @datevariable
Result: 2008-08-15

TIME 

 
TIME is stored in the format: hh:mm:ss.nnnnnnn, with a range of 00:00:00.0000000 through
23:59:59:9999999 and is accurate to 100 nanoseconds. Storage depends on the precision and scale selected, and runs from 3 to 5 bytes.

--Sample TIME output
DECLARE @timevariable as TIME
SET @timevariable = getdate()
PRINT @timevariable
Result: 14:26:52.3100000

DATETIME2

DATETIME2 is very similar to the older DATETIME data type, but has a greater range and
precision. The format is YYYY-MM-DD hh:mm:ss:nnnnnnnm with a range of 0001-01-01
00:00:00.0000000 through 9999-12-31 23:59:59.9999999, with an accuracy of 100 nanoseconds. depends on the precision and scale selected, and runs from 6 to 8 bytes.

--Sample DATETIME2 output with a precision of 7
DECLARE @datetime2variable datetime2(7)
SET @datetime2variable = Getdate()
PRINT @datetime2variable
Result: 2008-08-15 14:27:51.5300000

DATETIMEOFFSET

DATETIMEOFFSET is similar to DATETIME2, but includes additional information to track the
time zone. The format is YYYY-MM-DD hh:mm:ss[.nnnnnnn] [+|-]hh:mm with a range of 0001-
01-01 00:00:00.0000000 through 0001-01-01 00:00:00.0000000 through 9999-12-31 23:59:59.9999999. Universal Time (UTC), with an accuracy of 100 nanoseconds. Storage depends on the and scale selected, and runs from 8 to 10 bytes. zone aware means a time zone identifier is stored as a part of DATETIMEOFFSET column. time zone identification is represented by a [-|+] hh:mm designation. A valid time zone falls in range of -14:00 to +14:00, and this value is added or subtracted from UTC to obtain the local 

 --Sample DATETIMEOFFSET output with a precision of 0
--Specify a date, time, and time zone
DECLARE @datetimeoffsetvariable DATETIMEOFFSET(0)
SET @datetimeoffsetvariable = '2008-10-03 09:00:00 -10:00'
--Specify a different date, time and time zone
DECLARE @datetimeoffsetvariable1 DATETIMEOFFSET(0)
SET @datetimeoffsetvariable1 = '2008-10-04 18:00:00 +0:00'

 
--Find the difference in hours between the above dates, times,
--and timezones
SELECT DATEDIFF(hh,@datetimeoffsetvariable,@datetimeoffsetvariable1)
Result: 23


Spatial

While spatial data has been stored in many SQL Server databases for many years (using conventional data types), SQL Server 2008 introduces two specific spatial data types that can make it easier for developers to integrate spatial data in their SQL Server-based applications. In addition, by storing spatial data in relational tables, it becomes much easier to combine spatial data with other kinds of business data. For example, by combining spatial data (such as longitude and latitude) with the physical address of a business, applications can be created to map business locations on a map.
The two new spatial data types in SQL 2008 are:

• GEOMETRY: Used to store planar (flat-earth) data. It is generally used to store XY coordinates that represent points, lines, and polygons in a  two-dimensional space. For example storing XY coordinates in the GEOMETRY data type can be used to map the exterior of a building.

• GEOGRAPHY: Used to store ellipsoidal (round-earth) data. It is used to store latitude and longitude coordinates that represent points, lines, and polygons on the earth’s surface. For example, GPS data that represents the lay of the land is one example of data that can be stored
in the GEOGRAPHY data type.

GEOMETRY and GEOGRAPHY data types are implemented as .NET CLR data types. This means that they can support various properties and methods specific to the data. For example, a method can be used to calculate the distance between two GEOMETRY XY coordinates, or the distance between two GEOGRAPHY latitude and longitude coordinates. Another example is a method to see if two spatial objects intersect or not. Methods defined by the Open Geospatial Consortium standard, and Microsoft extensions to that standard, can be used. To take full advantage of these methods, you will have to be an expert in spatial data.Another feature of spatial data types is that they support special spatial indexes. Unlike conventional indexes, spatial indexes consist of a grid-based hierarchy in which each level of the index subdivides the grid sector that is defined in the level above. But like conventional indexes, the SQL Server query optimizer can use spatial indexes to speed up the performance of queries that return spatial data.Spatial data is an area unfamiliar to many DBAs. If this is a topic you want to learn more about, you will need a good math background, otherwise you will get lost very quickly.


HIERARCHYID
While hierarchical tree structures are commonly used in many applications, SQL Server has, up to not made it easy to represent and store them in relational tables. In SQL Server 2008, the HIERARCHYID data type has been added to help resolve this problem. It is designed to store that represent the position of nodes in a hierarchal tree structure. For example, the HIERARCHYID data type makes it easier to express the following types of relationships without requiring multiple parent/child tables and complex joins:

• Organizational structures
• A set of tasks that make up a larger projects (like a GANTT chart)
• File systems (folders and their sub-folders)
• A classification of language terms
• A bill of materials to assemble or build a product
• A graphical representation of links between web pages

Unlike standard data types, the HIERARCHYID data type is a CLR user-defined type, and it exposes many methods that allow you to manipulate the date stored within it. For example, there are methods to get the current hierarchy level, get the previous level, get the next level, and many more. In fact, the HIERARCHYID data type is only used to store hierarchical data; it does not automatically represent a hierarchical structure. It is the responsibility of the application to create and assign HIERARCHYID values in a way that represents the desired relationship. Think of a HIERARCHYID data type as a place to store positional nodes of a tree structure, not as a way to create the tree structure.

FILESTREAM
SQL Server is great for storing relational data in a highly structured format, but it has never been particularly good at storing unstructured data, such as videos, graphic files, Word documents, Excel spreadsheets, and so on. In the past, when developers wanted to use SQL Server to manage such unstructured data, they essentially had two choices:

• Store it in VARBINARY(MAX) columns inside the database
• Store the data outside of the database as part of the file system, and include pointers inside a column that pointed to the file’s location. This allowed an application that needed access to the file to find it by looking up the file’s location from inside a SQL Server table.Neither of these options was perfect. Storing unstructured data in VARBINARY(MAX) columns offers less than ideal performance, has a 2 GB size limit, and can dramatically increase the size of a database. Likewise, storing unstructured data in the file system requires the DBA to overcome several difficulties. 

For example:

• Files have a unique naming system that allows hundreds, if not thousands of files to be keep track of and requires very careful management of the folders to store the data.
• Security is a problem and often requires using NTFS permissions to keep people from accessing the files inappropriately.
• The DBA has to perform separate backups of the database and the files
• Problems can occur when outside files are modified or moved and the database is not updated to reflect this.

To help resolve these problems, SQL Server 2008 has introduced what is called FILESTREAM storage, essentially a hybrid approach that combines the best features of the previous two options.

Benefits of FILESTREAM
FILESTREAM storage is implemented in SQL Server 2008 by storing VARBINARY(MAX) binary large objects (BLOBs) outside of the database and in the NTFS file system. While this sounds very similar to the older method of storing unstructured data in the file system and pointing to it from a column, it is much more sophisticated. Instead of a simple link from a column to an outside file, the SQL Server Database Engine has been integrated with the NTFS file system for optimum performance and ease of administration. For example, FILESTREAM data uses the Windows OS system cache for caching data instead of the SQL Server buffer pool. This allows SQL Server to do what it does best: manage structured data, and allows the Windows OS to do what is does best: manage large files. In addition, SQL Server handles all of the links between database columns and the files, so we don’t have to. In addition, FILESTREAM storage offers these additional benefits:

• Transact-SQL can be used to SELECT, INSERT, UPDATE, DELETE FILESTREAM data.
• By default, FILESTREAM data is backed up and restored as part of the database file. If you want, there is an option available so you can backup a database without the FILESTREAM data.
• The size of the stored data is only limited by the available space of the file system. Standard VARBINARY(MAX) data is limited to 2 GB.

Limitations of FILESTREAM
As you might expect, using FILESTREAM storage is not right for every situation. For example, it is best used under the following conditions:

• When the BLOB file sizes average 1MB or higher.
• When fast read access is important to your application.
• When applications are being built that use a middle layer for application logic.
• When encryption is not required, as it is not supported for FILESTREAM data. If your application doesn’t meet the above conditions, then using the standard VARBINARY(MAX) data type might be your best option. If you are used to storing binary data inside your database, or outside your database (but using pointers inside the database that point to the binary files), then you will find using FILESTREAM storage to be substantially different. You will want to thoroughly test your options before implementing one option or the other, in any new applications you build. 

How to Implement FILESTREAM Storage Enabling SQL Server to use FILESTREAM data is a multiple-step process, which includes:

• Enabling the SQL Server instance to use FILESTREAM data
• Enabling a SQL Server database to use FILESTREAM data
• Creating FILESTREAM-enabled columns in a table, by specifying the "VARBINARY(MAX) FILESTREAM" data type.