The document discusses distributed database systems, which allow data to be stored across multiple physical locations, enhancing reliability, scalability, and performance. It outlines types of distributed databases, architectural models, key components such as data replication and fragmentation, and various data distribution techniques. It also highlights challenges like network latency and management complexity while emphasizing the need for proper planning to realize the benefits of distributed databases.

1. TAKSHASHILA UNIVERSITY
SCHOOL OF COMPUTER SCIENCE
DISTRIBUTED DATABASE SYSTEM
SUBMITTED BY: SUBMITTED TO:
R.ABIGAIL KALYANI MRS.R.SARANYA(MCA,M.PHIL,B.ED…,)
S.ABINESH ASSISTANT PROFESSOR
MCA(DS)-YEAR 1 TAKSHASHILA UNIVERSITY
TAKSHASHILA UNIVERSITY

2. AGENDA
INTRODUCTION
IMPORTANCE
OF DISTRIBUTED
DATABASE
TYPES
ARCHITECTURE
MODELS
KEY
COMPONENTS
DATA
DISTRIBUTION
TECHNIQUES
CHALLENGES CONCLUSION

3. INTRODUCTION
• A DISTRIBUTED DATABASE IS A
DATABASE THAT CONSIST OF
DATA STORED STORED AT
MULTIPLE PHYSICAL LOCATIONS.
• EVERY SINGLE DATABASE STORED
IN ONE NETWORK. USER CAN
ACCESS FROM ANYWHERE.

4. IMPORTANCE:
RELIABILITY:
DATA CAN BE
REPLICATED
ACROSS
MULTIPLE
NODES,
PROVIDING
HIGH
RELIABILITY.
SCALABILITY:
EASY TO ADD
MORE NODES TO
HANDLE
INCREASED
LOADS
PERFORMANCE:
ABILITY TO
PROCESS
QUERIES IN
PARALLEL
ACROSS
DISTRIBUTED
NODES.

5. TYPES:
• HOMOGENEOUS : SAME
STRUCTURE AND DBMS ACROSS
ALL NODES. EASIER MANAGEMENT
AND UNIFORMITY.
• HETEROGENEOUS :DIFFERENT
DBMS, STRUCTURES OR
MODELS.ALLOWS INTEGRATION OF
DIVERSE SYSTEMS BUT REQUIRES
MORE COMPLEX MANAGEMENT.

6. ARCHITECTURE
MODELS:
• CLIENT SERVER ARCHITECTURE: CLIENT
SEND REQUEST TO A CENTRALIZED SERVER ,
WHICH PROCESSES AND RESPONDS.
• PEER-TO-PEER: EACH PARTICIPANT NODE
ACT AS BOTH CLIENT AND SERVER , SHARING
RESOURCES EQUALLY.

7. KEY COMPONENTS:
DATA REPLICATION:
COPIES OF DATA STORED
AT MULTIPLE NODES FOR
BACKUP AND
RELIABILITY.
01
DATA
FRAGMENTATION:
DIVIDING THE DATABASE
INTO SMALLER PARTS FOR
EFFICIENT DISTRIBUTION.
02
MIDDLEWARE:
SOFTWARE THAT
ENABLES
COMMUNICATION AND
DATA MANAGEMENT
BETWEEN DISTRIBUTED
SYSTEMS.
03

8. DATA
DISTRIBUTIO
N
TECHNIQUES:
• HORIZONTAL PARTITIONING: ROWS OF A
DATASET ARE DISTRIBUTED ACROSS NODES.
• VERTICAL PARTITIONING:DIFFERENT
COLUMNS ARE STORED IN DIFFERENT
NODES.
• HYBRID PARTITIONING: A COMBINATION OF
THE TWO METHODS ABOVE FOR OPTIMIZED
PERFORMANCE.

9. CHALLENGES:
• NETWORK LATENCY:
KEEPING
DATA SYNCHRONIZED CAN BE
COMPLEX.
• NETWORK CONSISTENCY:
KEEPING
DATA SYNCHRONIZED CAN BE
COMPLEX.
• INCREASED COMPLEXITY:
MORE COMPONENTS
CAN LEAD TO MANAGEMENT AND
MAINTAINANCE CHALLENGES.

10. CONCLUSION:
• DISTRIBUTED DATABASE ARCHITECTURE ENABLES EFFICIENT DATA
MANAGEMENT ACROSS MULTIPLE LOCATIONS , OFFERING BENEFITS
SUCH AS SCALABILITY , BUT IT ALSO INVOLVES CHALLENGES THAT
REQUIRE CAREFUL PLANNING AND EXECUTION.