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