Specialized Database Presentation+Final
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Transcript of Specialized Database Presentation+Final
Specialized Database
Antony Biagianti DBM/384
December 22, 2014Brando Sumayao
StudySummary
Database MatrixDatabases Purposes Similarities Differences
Relational A set of tables that store
related information.
• Reduced application development
time
• Data independence
• Uniform data administration
• Declarative query languages
• Data integrity and security
• Relational data model.
• constraints that enforce data integrity.
• Ad hoc relationship can also be used.
• Normalized to eliminate data replication
Specialty An extended relational
model database that
support complex
multidimensional data
• Relational schemas
• Use of Keys
• Use of indexes
• Join operations
• Querying process
• High protection
• Object-relational model
• Complex data types
• Composite attributes
• Constructor functions
• Self-referential attribute
Parallel Originated to run
multiple instances that
share a single physical
database
• Querying
• Data Integration
• Data Sharing
• Security
• Designed for large storage
• Executes tasks concurrently on several
nodes
• Task Synchronization
• Sharing of resources.
• Uses Speedup and Scaleup
Distributed Collections of data in the
database can be
distributed across
multiple physical
locations.
• Relational Schemas
• Uses Tables
• Use of Keys
• Use of Indexes
• Querying Process
• Denormalized
• Duplicate Data
• Optimized for Queries
• Subject Oriented
• Multiple Data Feeds
• Complex Queries
Data
Warehouse
Designed to analyze data
typically historical in
nature that can be used by
businesses to project
trending in such areas as
sales, productivity, and
expenditures.
• Relational Schemas
• Uses Tables
• Use of Keys
• Use of Indexes
• Querying Process
• Denormalized
• Duplicate Data
• Optimized for Queries
• Subject Oriented
• Multiple Data Feeds
• Non-Volatile
SQL ConceptsSQL Concept Spatial Temporal Business Use
PostgreSQLGiST (Generalized Search
Tree) index is a balanced
tree-structured method that
performance enhancing
indices can be built on to
support spatial data.
Uses basic SQL date/time
functions which returns
start time using current
statements.
• Government
• Finance
• Corporations
• Gaming
OracleAn Oracle database is data
that is treated as one unit.
Oracle Database 12c
supports the Temporal
database feature which
was introduced in ANSI
SQL:2011.
• HR/Payroll
• Access cash management and operational
effectiveness of the payable department.
• Identify profitable customers.
• Manager monetary performance in multiple
locations.
IBM DB2 IBM DB2 is a database of
choice because it has
enterprise-wide solutions for
handling high-volume
workloads.
SQL compatibility
minimizes the cost and
risk of moving legacy
apps built for Oracle
DB2. Uses pureXML for
storage, processing, and
management of XML
data.
• DB2 for Linus, Unix and Windows
• DB2 Connect (connects desktop and palm-top
apps to the mainframe and minicomputer host
databases.
• Optimized for SOA, CRM and data
warehousing.
MS SQL
Server
MS SQL’s approach is to
store data as two types;
Geometry is stored as planar
or flat earth data comprised
of x-y coordinates
representing two
dimensional points, lines and
polygons on the earth as a
flat surface.
The new ANSI/ISO
standard allows SQL
server to maintain a
higher degree of time
date accuracy. This
higher degree of accuracy
lends to the temporal
capabilities of MS SQL
Server
• Business uses for MS SQL server include
most Microsoft applications.
• For Financial applications there is Microsoft
Great Plains/Dynamics.
• Customer relations management or MS CRM
uses a SQL backend as does MS SharePoint
TEMPORAL
SPATIAL
INFORMATION RETRIEVAL
OLTP
OLAP
Knowledge Management
KM
Identify
Capture
EvaluateRetrieve
Share
Strive to hit the mark!
Conclusion
REFERENCEBashfield, A. (2009 July 3). Oracle Spatial Databases. Retrieved from
http://www.slideshare.net/andrew_bashfield/oracle-spatial-databases-1677284
Bogue, L, R. (2005). An introduction to the benefits of online analytical processing (OLAP). Retrieved from
http://www.techrepublic.com/article/an-introduction-to-the-benefits-of-online-analytical-processing-olap/
DbaNotes. (2014 June, 25). Oracle 12c Temporal Database. Retrieved from
http://www.dbanotes.com/oracle-database/oracle-12c-temporal-database/
Frakes, William B. (1992). Information Retrieval Data Structures and Algorithms. Prentice-Hall, Inc. ISBN 0-13-463837-9.
Koenig, D, E, M. (2012). What is KM? Knowledge Management explained. Retrieved from
http://www.kmworld.com/Articles/Editorial/What-Is-.../What-is-KM-Knowledge-Management-Explained-82405.aspx
NTC. (2014). SQL (Structured Query Language). Retrieved from http://www.ntchosting.com/encyclopedia/databases/structured-
query-language/
Silberschatz, A., Korth, H., & Sudarshan, S. (2011). Database System Concepts (6th ed.). New York, NY: McGraw-Hill.
Technopedia. (2014). Online analytical processing (OLAP). Retrieved from http://www.techopedia.com/definition/1225/online-
analytical-processing-olap
Tutorialspoint, (2014). PostgreSQL - DATE/TIME Functions and Operators. Retrieved from
http://www.tutorialspoint.com/postgresql/postgresql_date_time.htm
Obe, R. & Hsu, L. (2010 July 7). PostGIS in Action. Retrieved from
http://www.manning.com/obe/PostGIS_MEAPCH01.pdf