This document discusses heterogeneous database systems. It defines a heterogeneous database system as an automated or semi-automated system that integrates disparate database management systems to present a unified query interface to users. It discusses issues in multi-database query processing such as query support, cost, translation and change adaptation. The architecture involves individual databases, wrapper methods, a mediator and query processing/optimization. Database integration involves schema integration through a bottom-up design approach and the conversion of local schemas to a global schema.

1. -Akash Mukherjee 75
-Raj Manjrekar 63
-Ravikumar Kamma 47
-Shreyank Joshi 42

2. Introduction
 Concept:
 Collection of many logically related databases
 Need of well accepted standards for construction
 Examples:
 ODBC connection
 JDBC connection

3. Definition
A heterogeneous database system is an
automated (or semi-automated) system
for the integration of heterogeneous,
disparate database management system
to present a user with a single, unified
query interface.

4. Issues in Multi-Database Query
Processing
 Query Support
 Query Cost
 Query Translation
 Change Adaptation

5. Architecture
 Individual DB
 Wrapper methods
 Mediator
 Query processing and optimization

6. Database Integration
 Introduction
 Bottom-up design approach
 Schema integration
 Local to global schema conversion
 Either physical or logical level

7. Extract Transform
Load(ETL)

8. Schema Integration
 Introduction:
 Global Schema:
 Centralize global schema
 Centralize global schema with backup
 Replicated global schema
 Segmented global schema
 Issues of Schema integration
 Global schema maintenance
 Global schema creation

9. Schema Integration
 Process of schema integration
 Schema translation
 Export schema generation
 Schema integration
○ Pre-Integration
○ Discovery
○ Resolution
○ Merging
 Supplement database

10. Query Processing
 Overview
 Issues
 Heterogeneous cost model
○ Black box approach
○ Customized approach
○ Dynamic approach

11. Query Processing
 Query Optimization
○ Query based
○ Operator Based
 Adaptive query processing
○ Query mapping
○ Data localization
○ Global query optimization
○ Local query optimization

12. THANK YOU