Distributed Databases: Concepts, Advantages, and Strategies, Study notes of Database Management Systems (DBMS)

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Data Communication

Distributed and Centralized computing

Definitions



Distributed Database: A single logical

database spread physically across computers in multiple locations that are connected by a data communications link  Decentralized Database: A collection of independent databases on non-networked computers They are NOT the same thing!

Figure 13-1 Distributed database environments (adapted from Bell and Grimson, 1992)

Distributed Database

Options

 (^) Homogeneous–same DBMS at each node  (^) Autonomous–independent DBMSs  (^) Non-autonomous–central, coordinating DBMS  (^) Easy to manage, difficult to enforce  (^) Heterogeneous–different DBMSs at different nodes  (^) Systems–with full or partial DBMS functionality  (^) Gateways–simple paths are created to other databases without the benefits of one logical database  (^) Difficult to manage, preferred by independent organizations

Identical DBMSs Figure 13-2 Homogeneous Distributed Database Environment Source : adapted from Bell and Grimson, 1992.

Typical Heterogeneous

Environment

 Data distributed across all the nodes  Different DBMSs may be used at each node  Local access is done using the local DBMS and schema  Remote access is done using the global schema

Major Objectives

 (^) Location Transparency  (^) User does not have to know the location of the data  (^) Data requests automatically forwarded to appropriate sites  (^) Local Autonomy  (^) Local site can operate with its database when network connections fail  (^) Each site controls its own data, security, logging, recovery

Significant Trade-Offs

 (^) Synchronous Distributed Database  (^) All copies of the same data are always identical  (^) Data updates are immediately applied to all copies throughout network  (^) Good for data integrity  (^) High overhead  slow response times  (^) Asynchronous Distributed Database  (^) Some data inconsistency is tolerated  (^) Data update propagation is delayed  (^) Lower data integrity  (^) Less overhead  faster response time NOTE: all this assumes replicated data (to be discussed lat

Disadvantages of

Distributed Database

Compared to

Centralized Databases

 Software cost and complexity  Processing overhead  Data integrity exposure  Slower response for certain queries

Options for

Distributing a Database

 Data replication  (^) Copies of data distributed to different sites  Horizontal partitioning  (^) Different rows of a table distributed to different sites  Vertical partitioning  (^) Different columns of a table distributed to different sites  Combinations of the above

Data Replication (cont.)

 Disadvantages:  (^) Additional requirements for storage space  (^) Additional time for update operations  Complexity and cost of updating  Integrity exposure of getting incorrect data if replicated data is not updated simultaneously Therefore, better when used for non-volatile Therefore, better when used for non-volatile (read-only) (read-only) datadata

Types of Data Replication

 Push Replication–  updating site sends changes to other sites  Pull Replication–  receiving sites control when update messages will be processed

Factors in Choice of

Distributed Strategy

 Funding, autonomy, security  Site data referencing patterns  Growth and expansion needs  Technological capabilities  Costs of managing complex technologies  Need for reliable service