Difference between Parallel and Distributed databases

Last Updated : 18 Sep, 2024

Parallel and Distributed Databases are significant components within an enormous quantity of big data processing since they help to enhance data handling in terms of efficiency and expandability. Nonetheless, there is sometimes confusion between them because both are aimed at achieving the most effective solution to the organization’s handling of its data. This article lays out the definition of parallel and distributed databases, their functionality, and pros and cons to give you an insight into what system is more desirable for use in certain cases.

What is Parallel Database?

A parallel DBMS is a DBMS that runs across multiple processors and is designed to execute operations in parallel, whenever possible. The parallel DBMS links several smaller machines to achieve the same throughput as expected from a single large machine.

Features

There are parallel working of CPUs
It improves performance
It divides large tasks into various other tasks
Completes work very quickly

Advantages of Parallel Databases

Increased Speed and Efficiency: That is why the application of parallel databases allows executing several queries at the same time and consequently, decreases the total amount of time needed for processing them.

Improved Resource Utilization: Most of them take advantage of the multi-processor architecture, thus using as many CPU cores as possible.

High Throughput: They perform a large number of computations in less time more than the sequential methods hence suitable for large-scale uses.

Disadvantages of Parallel Databases

Complexity in Maintenance: Indeed, employment of parallel databases might be slightly problematic as synchronization and some other components of the processes are worthy of special attention.

Higher Costs: While parallel databases may be defined with robust physical databases which require intensive hardware the databases may be more costly in setting up and even in operation.

What is Distributed Database?

A Distributed database is defined as a logically related collection of data that is shared which is physically distributed over a computer network on different sites. The Distributed DBMS is defined as, the software that allows for the management of the distributed database and makes the distributed data available for the users.

Features

It is a group of logically related shared data
The data gets split into various fragments
There may be a replication of fragments
The sites are linked by a communication network

The main difference between the parallel and distributed databases is that the former is tightly coupled and then later loosely coupled.

Advantages of Distributed Databases

Fault Tolerance: Since the data is distributed to various centers, failure in one center does not result to the total failure of the system.
Scalability: Due to the ability of distributed databases, it can easily be scaled up by adding nodes to the network which makes it ideal for businesses that are expanding.
Local Autonomy: Every site can administer a separate data base, however they are all in the collective database at the same time.

Disadvantages of Distributed Databases

Complex Data Management: Sharing data with multiple facilities presents some problems like latency of data.
Security Concerns: The more the places there is data stored the higher the risk of breaches hence the need to enforce very strict security measures.