This document discusses new capabilities in SQL Server 2012 for managing both structured and unstructured data. It notes challenges with building applications that use different data formats. SQL Server 2012 aims to reduce costs and simplify development by providing common application models, constructs and services for all types of data. It allows for storage and querying of various data formats natively and consistently. The document outlines new programmability options and rich services for search, spatial data, XML and more. It also shows how SQL Server 2012 provides efficient storage, high throughput access and integrated administration for all data.

2. Structured and
unstructured Search
Related/”Semantic”
Search

3. Building and Maintaining Applications with
relational and non-relational data is hard
Pain Complex integration
Duplicated functionality
Points Compensation for unavailable services
Reduce the cost of managing all data
Simplify the development of applications
Goals over all data
Provide management and programming
services for all data

4. Tables, XML, Spatial, Documents, Digital Media, Scientific
Records, Factoids…
Data formats and content natively understood for rich application and
user experience
Consistent Application Model and Data Constructs to ease application
development, migration and long-term retention
Provide rich services, e.g.,

5. Programmability
T-SQL
Query
Structured
Data
B-trees
Manageability
Availability
Files

6. Programmability
T-SQL
Query Search
Structured Unstructured
Data Data
B-trees
Manageability
Availability
Files

7. Programmability
Spatial, XML,
T-SQL/Data Types HierarchyID
Win 32
Query and XQuery
Search
Type Operations Spatial ops
Semi-
Structured Unstructured
structured
Data Data
Data/XML
XML, FTS, Spatial
B-trees Indices
Filestrea
Manageability m
Availability
Files

8. Rich Data Programmability
Programming
Spatial, XML,
Capabilities T-SQL/Data Types HierarchyID
Win 32
Rich Query and Query and Type
Search
Search Services Operations
XQuery
over all Data Spatial ops Semantic
Platform
Efficient Storage Structured Semi-structured Unstructured
for BR Data Data Data/XML Data
XML, FTS, Spatial
B-trees Indices
Filestream
Manageability& Availability
Files

11. Transactional Access Streaming Win32 Access
Streaming Win32 Access??
Database Applications Windows Apps SQL Apps
Blobs SMB Share FileStream
Files/Folders API
Rich Services
Fulltext Search Database
Solutions
Scale-up
Semantic Similarity Disk Disk Disk
FileTable
1 2 3
FileStreams
Search
Multiple Containers
Integrated Administration?
Integrated Administration Remote BLOB Storage
Customer Application
SQL RBS API
D
D Centera SQL
B FileStre Azure lib lib FILESTREAM lib
B FileStreams
Integrated Azure Centera SQL DB
Backup/Replication/AlwaysOn

12. Store BLOBs in
DB + File System
Application
BLOB
DB

13. FileTable Folder Hierarchy
FILESTREAM
Share
MSSQLSERVER
my_machine
Database MSSQLSERVEROffice
Directories DocsDocuments
Private Docs Office Docs
(Database1) (Database2)
FileTable
Directories
Media Documents LogFiles
(FileTable) (FileTable) (FileTable)
User-Defined
Directory
Structure

15. 900
800
700
Filestream Win32
(Filesystem)
Throughput (Mbps)
600 Access
Filestream T-SQL
500
400 Varbinary
300
Filesystem Win32
200 Access Gain (%)
100
0
240 KB 480 KB 1 MB 2 MB 4 MB 8 MB

16. Insert
600
Filestream
500 Win32
(Filesystem)
400 Access
Filestream T-
Throughput (Mbps)
300 SQL
200
Varbinary
100
0
240 KB 480 KB 1 MB 2 MB 4 MB 8 MB
-100
-200

17. Create/Alter Database
max_size
DBCC Shrinkfile Emptyfile

18. Use of multiple spindles for achieving better I/O Scalability

19. 2012 2012

22. Queries over 350M documents database and random DMLs running in background.
Beating SQL Server 2005 with a scale factor more than 2x and with avg 60x times better throughput

23. 2005/8 vs 2012
2005/8
2012
Query avgExecTime (ms) under various number of connections (50 ~ 2000 users) for customer
playback benchmark

25. geography::Point(lat, lon, 4326)

27. C
B D A B A B
D A
Primary Filter Secondary Filter
E (Index lookup) (Original predicate)
In general, split predicates in two
Primary filter finds all candidates, possibly
with false positives (but never false negatives)
Secondary filter removes false positives
The index provides our primary filter
Original predicate is our secondary filter
Some tweaks to this scheme
Sometimes possible to skip secondary filter

28. Fully contained
cells
Partially
contained cells

32. Optimal value (theoretical) is
somewhere between two extremes
Default values: Time needed to
512 - Geometry AUTO grid process false positives
768 - Geography AUTO grid
1024 - SELECT * FROM table t WITH
MANUAL grids (SPATIAL_WINDOW_MAX_CELLS=256)
WHERE t.geom.STIntersects(@window)=1;

35. CREATE SPATIAL INDEX idxGeog
ON table(geography column)
USING GEOGRAPHY_GRID
WITH (
DATA_COMPRESSION = page | row
);
On the basis of internal tests, with compression
- 40%-50% smaller
- 20% faster -15% slower queries
- Per partition compression setting is not supported.

37. Give me the closest 5 Italian restaurants
SQL Server 2008/2008 R2: table scan
SQL Server 2012: uses spatial index
SELECT TOP(5) *
FROM Restaurants r
WHERE r.type = ‘Italian’
AND r.pos.STDistance(@me) IS NOT NULL
ORDER BY r.pos.STDistance(@me)

39. Find the closest 50 business points to a specific location (out of 22 million in total)

42. http://www.slideshare.net/MichaelRys/sql-bits-brruds
http://www.slideshare.net/MichaelRys/filetable-and-semantic-search-in-sql-server-2012
http://www.sqlserverlaunch.com/WW/theater?sid=634
http://www.slideshare.net/MichaelRys/sqlbits-x-sql-server-2012-spatial
http://www.slideshare.net/MichaelRys/sqlbits-x-sql-server-2012-spatial-indexing
Forum:
http://forums.microsoft.com/MSDN/ShowForum.aspx?ForumID=1629&SiteID=1