Framework of distributed database design
The framework of distributed database design can be divided into three main phases:
Data fragmentation: This phase involves dividing the data into smaller pieces that can be stored on different computers. There are two main types of data fragmentation:
Horizontal fragmentation: This involves dividing the data into rows. For example, a table of customer records could be horizontally fragmented by customer ID.
Vertical fragmentation: This involves dividing the data into columns. For example, a table of customer records could be vertically fragmented by customer name, customer address, and customer phone number.
Data placement: This phase involves deciding where to store the fragmented data. There are two main factors to consider when placing data:
Data locality: This refers to the tendency of users to access data that is stored on the same computer as they are.
Data availability: This refers to the need to make sure that all of the data is available to all users, even if some of the computers are unavailable.
Data replication: This phase involves creating copies of the data on multiple computers. Data replication can be used to improve data availability and to improve performance.
Factors to consider in distributed database design
There are a number of factors to consider when designing a distributed database, including:
The size of the database: The larger the database, the more important it is to distribute the data across multiple computers.
The number of users: The more users that will be accessing the database, the more important it is to make sure that the data is available and that the performance is good.
The type of data: Some types of data, such as real-time data, are more sensitive to latency than other types of data.
The budget: Distributed database design can be more expensive than designing a centralized database.
Benefits of distributed database design
There are a number of benefits to using a distributed database, including:
Scalability: Distributed databases can be scaled up or down easily as the need arises.
Availability: Distributed databases can be more available than centralized databases because if one computer goes down, the data can still be accessed from the other computers.
Performance: Distributed databases can often provide better performance than centralized databases because the data can be accessed from the computer that is closest to the user.
Security: Distributed databases can be more secure than centralized databases because the data is spread across multiple computers.
Drawbacks of distributed database design
There are a number of drawbacks to using a distributed database, including:
Complexity: Distributed database design can be more complex than designing a centralized database.
Cost: Distributed database design can be more expensive than designing a centralized database.
Latency: The latency of a distributed database can be higher than the latency of a centralized database.
Synchronization: It can be more difficult to keep the data in a distributed database synchronized than in a centralized database.
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