View stunning SlideShares in full-screen with the new iOS app!Introducing SlideShare for AndroidExplore all your favorite topics in the SlideShare appGet the SlideShare app to Save for Later — even offline
View stunning SlideShares in full-screen with the new Android app!View stunning SlideShares in full-screen with the new iOS app!
SPOT DATABASES: EFFICIENT
CONSISTENCY CHECKING AND
OPTIMISTIC SELECTION IN
Presented By : Pratik S. Udapure
Features of Spatial Databases
Advantages of Spatial Databases
Disadvantages of Spatial Databases
Spatial database: is a database that is
optimized to store and query data that
represents objects defined in a geometric
It offers additional functions that allow
processing spatial data types.
Spatial Objects: Consists of lines, surfaces,
volumes and higher dimension objects that are
used in applications of computer-aided design,
cartography, geographic information systems.
Spatial Data: The values of the objects spatial
attributes (length, configuration, perimeter,
area, volume, etc.)
Optimizing spatial databases means
optimizing the queries, which requires less
time spent by running the queries before
receiving an answer.
Indexing Spatial Data: a mechanism to decrease the
number of searches (optimize spatial queries).
A Spatial Index is used to locate objects in the
same area of data or from different locations
Spatial indexes include:
Spatial Indexes: Grid Index
In the context of a Spatial Index, a grid (a.k.a. "mesh", also
"global grid" if it covers the entire surface of the globe) is a
regular division of a 2-D surface that divides it into a series
of contiguous cells, which can then be assigned unique
identifiers and used for spatial indexing purposes.
Spatial Indexes: Z-Order
In mathematical analysis and computer
science, Z-order, Morton order, or Morton code
is a function which maps multidimensional
data to one dimension while preserving locality
of the data points.
Spatial Indexes: Octree
An octree is a tree data structure in which each
internal node has exactly eight childern. Octrees
are most often used to partition a three dimensional
space by recursively subdividing it into eight octants
Spatial Indexes: Quad Tree
A quadtree is a tree data structure in which
each internal node has exactly four children.
Quadtrees are most often used to partition a
two-dimensional space by recursively
subdividing it into four quadrants or regions.
Spatial Indexes: UB Tree
The UB-tree as proposed by Rudolf Bayer and Volker
Markl is a balanced tree for storing and efficiently
retrieving multidimensional data. It is basically a B+tree
(information only in the leaves) with records stored
according to z-order, also called Morton order. Z-order is
simply calculated by bitwise interlacing the keys.
Spatial Indexes: R Tree
R-trees are tree data structure used for spatial
access methods,i.e., for indexing multi-
dimensional information such as geographical
coordinates, rectangles or polygons.
Spatial Indexes: KD Tree
The k-d tree is a binary tree in which every node
is a k-dimensional point. Every non-leaf node can
be thought of as implicitly generating a splitting
hyperlane that divides the space into two parts,
Spatial Indexes: M Tree
M-trees are tree data structure that are similar to
R-trees and B-trees. As in any Tree-based data
structure, the M-Tree is composed of Nodes and
Leaves. In each node there is a data object that
identifies it uniquely and a pointer to a sub-tree
where its children reside. Every leaf has several
A spatial query is a special type of database
query supported by geo databases and spatial
Some of the most important are that they allow
for the use of geometry data types such as
points, lines and polygons and that these
queries consider the spatial relationship
between these geometries.
insert into pubs values ('Garricks Head',4.50,
GeometryFromText('POINT (1196131 383324)’,2167));
select name, beer-price, distance(location,
from pubs order by beer-price;
name | beer-price | distance
Fireside | 4.25 | 1484.10275160491
The Forge | 4.33 | 1533.06561109862
Rumours | 4.46 | 2042.00094093097
Garricks Head | 4.5 | 669.389105609889
Slap Happy | 4.5 | 1882.31910168298
Old Bailys | 4.55 | 1147.20900404641
Black Sheep | 4.66 | 536.859935972633
Big Bad Daves | 4.75 | 907.446543878884
Features of spatial databases
Spatial Measurements: Computes line length, polygon
area, the distance between geometries, etc.
Spatial Functions: Modify existing features to create new
ones, for example by providing a buffer around them,
intersecting features, etc.
Spatial Predicates: Allows true/false queries about
spatial relationships between geometries. Examples
include "do two polygons overlap" or 'is there a
residence located within a mile of the area we are
planning to build the landfill?'
Geometry Constructors: Creates new geometries,
usually by specifying the vertices (points or nodes)
which define the shape.
Observer Functions: Queries which return specific
information about a feature such as the location of the
center of a circle
Advantages of Spatial
Able to treat your spatial data like anything else in the DB
less data redundancy
fundamental organization and operations handled by the DB
Spatial querying using SQL
use simple SQL expressions to determine spatial
use simple SQL expressions to perform spatial
Disadvantages of Spatial
Cost to implement can be high
Incompatibilities with some GIS software
Slower than local, specialized data structures
User/managerial inexperience and caution
Spatial Databases are widely used nowadays.
Optimizing Spatial Databases is of a
Spatial databases can be optimized using
spatial indexes like R-tree or Quadtree and
other indexing structures.
Big career opportunities in Spatial DB sector
in developing GIS software