A distributed database is a database system that spans multiple computers or nodes that are connected by a network. Each node in a distributed database can store a portion of the data, and the entire database is made up of the sum of the data stored on each node.

In a distributed database, data is stored and processed in a distributed manner, and the system ensures that the data remains consistent and available to users despite network failures or other system errors. The primary goal of a distributed database is to provide high availability, scalability, and performance to applications that require access to large amounts of data.

Need of Distributed Database In Dbms

Let's start with the databases and their types,

A database is an structured collection of information. The data can be easily accessed, managed, modified, updated, controlled, and organized in a database.
Databases can be broadly classified into two types, namely Distributed and Centralized databases. The question here is why do we even need a Distributed Database In Dbms?. Let's assume for a moment that we have only centralized databases.
- We will be inserting all the data into one single database. Making it too large so that it will take a lot of time to query a single piece of record.
- Once a fault occurs, we no longer be able to serve user requests as we have only one database.
- No scaling is possible even if we wanted to and availability is also less which in turn affects the throughput.

Distributed databases resolve various issues, such as availability, fault tolerance, throughput, latency, scalability, and many other problems that can arise from using a single machine and a single database. That's why we need distributed databases. Let's discuss them in detail.

Distributed Databases

A distributed database is a database that is not limited to one computer system. It is like a database that consists of two or more files located in different computers or sites either on the same network or on an entirely different network.
These sites do not share any physical component. Distributed databases are needed when a particular data in the database needs to be accessed by various users globally. It needs to be handled in such a way that for a user it always looks like one single database.
By contrast, a Centralized database consists of a single database file located at one site using a single network.
Below is a reference diagram for distributed databases.

Types:

1. Homogeneous Database:
In a homogeneous database, all different sites store database identically. The operating system, database management system, and the data structures used – all are the same at all sites. Hence, they’re easy to manage.

2. Heterogeneous Database:
In a heterogeneous distributed database, different sites can use different schema and software that can lead to problems in query processing and transactions. Also, a particular site might be completely unaware of the other sites. Different computers may use a different operating system, different database application. They may even use different data models for the database. Hence, translations are required for different sites to communicate.

Architectural Models

Some of the common architectural models are −

Client - Server Architecture for DDBMS
Peer - to - Peer Architecture for DDBMS
Multi - DBMS Architecture

Client - Server Architecture for DDBMS

This is a two-level architecture where the functionality is divided into servers and clients. The server functions primarily encompass data management, query processing, optimization and transaction management. Client functions include mainly user interface. However, they have some functions like consistency checking and transaction management.

The two different client - server architecture are −

Single Server Multiple Client
Multiple Server Multiple Client (shown in the following diagram)

Server Architecture

Peer- to-Peer Architecture for DDBMS

In these systems, each peer acts both as a client and a server for imparting database services. The peers share their resource with other peers and co-ordinate their activities.

This architecture generally has four levels of schemas −

Global Conceptual Schema − Depicts the global logical view of data.
Local Conceptual Schema − Depicts logical data organization at each site.
Local Internal Schema − Depicts physical data organization at each site.
External Schema − Depicts user view of data.

Peer- to-Peer Architecture

Multi - DBMS Architectures

This is an integrated database system formed by a collection of two or more autonomous database systems.

Multi-DBMS can be expressed through six levels of schemas −

Multi-database View Level − Depicts multiple user views comprising of subsets of the integrated distributed database.
Multi-database Conceptual Level − Depicts integrated multi-database that comprises of global logical multi-database structure definitions.
Multi-database Internal Level − Depicts the data distribution across different sites and multi-database to local data mapping.
Local database View Level − Depicts public view of local data.
Local database Conceptual Level − Depicts local data organization at each site.
Local database Internal Level − Depicts physical data organization at each site.