Difference between Parallel and Distributed databases
1. 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 link a number of smaller machines to achieve the same throughput as expected from a single large machine.
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- There are parallel working of CPUs
- It improves performance
- It divides large tasks into various other tasks
- Completes works very quickly
2. 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.
- 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.
Difference between Parallel and Distributed databases : Parallel Database Distributed Database
In parallel databases, processes are tightly coupled and constitutes a single database system i.e., the parallel database is a centralized database and data reside in a single location In distributed databases, the sites are loosely coupled and share no physical components i.e., distributed database is our geographically departed, and data are distributed at several locations. In parallel databases, query processing and transaction is complicated. In distributed databases, query processing and transaction is more complicated in distributed database systems In parallel databases, it’s not applicable. In distributed databases, a local and global transaction can be transformed into distributed database systems In parallel databases, the data is partitioned among various disks so that it can be retrieved faster. In distributed databases, each site preserve a local database system for faster processing due to the slow interconnection between sites In parallel databases, there are 3 types of architecture: shared memory, shared disk, and shared shared-nothing. Distributed databases are generally a kind of shared-nothing architecture In parallel databases, query optimization is more complicated. In distributed databases, query Optimisation techniques may be different at different sites and are easy to maintain In parallel databases, data is generally not copied. In distributed databases, data is replicated at any number of sides to improve the performance of systems Parallel databases are generally homogeneous in nature Distributed databases may be homogeneous or heterogeneous in nature. Skew is the major issue with the increasing degree of parallelism in parallel databases. Blocking due to site failure and transparency are the major issues in distributed databases.