Question 3 Flashcards
What is a centralized DBMS?
All data and processing occur in one location, leading to easier management but potential performance bottlenecks and single points of failure.
What is a Distributed DBMS?
Data and processing are spread across multiple locations, enhancing performance and fault tolerance, but increasing complexity.
What is a Fully Distributed DBMS?
A system where both data and processing are completely distributed across nodes, with support for heterogeneous environments and the ability to function independently.
Name the three levels of data and process distribution.
- Single-Site Processing, Single-Site Data (SPSD)
- Multiple-Site Processing, Single-Site Data (MPSD)
- Multiple-Site Processing, Multiple-Site Data (MPMD)
What is Single-Site processing, Single-Site Data?
Description:
- All Data and Processing occur on a single host computer.
Key Features:
- Centralized processing and data storage.
- Limited to a single location.
Use Cases:
- Legacy systems, mainframes, and early microcomputers.
What is Multiple-Site Processing, Single-Site Data?
Description:
- Data is stored centrally, but processing happens across multiple computers.
Key Features:
- Increases network traffic due to the file transfers.
- Data processed remotely.
- Limited distributed capabilities.
Use Cases:
- Multi-user accounting applications, network file servers.
What is Multiple-Site Processing, Multiple-Site Data?
Description:
- Both data and processing are distributed across multiple sites.
Key Features:
- Fully distributed data and processes.
- Homogeneous or heterogeneous DBMs.
- Reduces Network Traffic
- Greater scalability
Use Cases:
- Fully Distributed DBMSs
What are DDBMS transparency features?
Make all the system’s complexities hidden from the end user. So the end user can continue working as if it were centralized, without having to be concerned about the decentralized nature of the DB.
What is distribution transparency?
Allows a distributed DB to be treated as a single logical DB. (The user does not need to know how the data is partitioned, geographically dispersed, or replicated among sites).
What is transaction transparency?
Allows a transaction to update data at more than one network site. (Ensures that a transaction will either be entirely completed or aborted to maintain DB integrity).
What is failure transparency?
Ensures that the system will continue to operate in the event of a node or network failure.
What is performance transparency?
Allows the system to perform as if it were a centralized DBMS. (It will not suffer performance degradation and will find the most cost-effective path to access remote data).
What is heterogeneity transparency?
Allows the integration of several different local DBMSs (relational, network, hierarchical) under a common or global schema
Discuss data fragmentation and strategies.
Data fragmentation: How to partition database into fragments
1. Horizontal Fragmentation: Divides a relation into subsets of tuples (rows). Each fragment contains unique rows and is stored at a different node.
2. Vertical Fragmentation: Divides a relation into subsets of attributes (columns). Each fragment contains unique columns, except for the key column, and is stored at a different node.
3. Mixed Fragmentation: Combines both horizontal and vertical fragmentation strategies.
Discuss data replication and strategies.
Data replication: Describes the process of deciding which fragments to replicate over multiple sites.
1. Fully replicated databases: Store copies of all data at multiple sites, though this can be impractical due to system overhead.
2. Partially replicated databases: Replicate only some data fragments at multiple sites, a more manageable approach.
3. Unreplicated databases: Store each fragment at only one site, with no duplicates.
