specialized database presentation+final
TRANSCRIPT
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Specialized Database
Antony Biagianti DBM/384
December 22, 2014Brando Sumayao
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StudySummary
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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
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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
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TEMPORAL
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SPATIAL
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INFORMATION RETRIEVAL
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OLTP
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OLAP
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Knowledge Management
KM
Identify
Capture
EvaluateRetrieve
Share
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Strive to hit the mark!
Conclusion
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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