Types of Database

Database has been advanced a lot throughout the span of the most recent half-century. Databases have been of various types over these years. Various different types of Databases are:

Object-oriented databases

Object-oriented databases (OODS) are databases that represent data in the form of objects and classes. In object-oriented terminology, an object is a real-world entity, and a class is a collection of objects. In object-oriented programing (OOPS), programming classes have member functions that show the properties of the database class. Example: PostgreSQL

File-Based databases

File-Based databases were first evolved in 1968. Data was put away as a flat file in file-based databases. It is the most basic storage technique with less security and management. Examples: Microsoft’s NTFS, and Apple’s Hierarchical File System.

Relational databases

A relational database is a collection of data items with pre-defined relationships between them. These items are organized as a set of tables with columns and rows. It become popular in the 1980s, and it gives the best and most flexible way to deal with access to organized/structured data. Examples: Oracle, MySQL, Microsoft SQLServer, PostgreSQL, and many more.

Distributed databases

A distributed database (DDB) is an integrated collection of databases that is physically distributed across sites in a computer network. In a Distributed database, the data is spread over numerous geographic regions to provide high accessibility and fast access. Examples: Apache Ignite, Apache Cassandra, Apache HBase, Amazon SimpleDB, MongoDB, etc.

Cloud databases

Cloud database permits you to store, guide/manage, and access structured (when you can store the data as rows and columns) and unstructured data(where we don’t store the data in rows and columns) over the web or a cloud platform. This data can be accessed over the internet. As they are offered as a managed service, cloud databases are also called databases as a service (DBaaS). Examples: AWS (Amazon Web Services) cloud administrations, Oracle Database Cloud Services, Google cloud spanner.

Open-source Databases

An open-source database system is one whose source code is available to people in general/public, these databases are SQL or NoSQL. Open Source contributions can be made by the public to work on(improve) the system’s functionalities, and these are free to use for everyone or can be accessed by the normal public. Example: SQL

Graph Databases

It addresses/represents the data as a chart or in the form of a graph. It is included nodes and edges. Each edge means a connection between two edges, and every node addresses an object. In a graph database, every node addresses a unique id. Real-life instances/examples of Graph Databases are social media applications and web applications. They show the connection between stored data and in social media applications, and friend suggestions algorithms also work on that data relations. Examples: MarkLogic, Microsoft SQL Server 2017.

Hierarchical database

A hierarchical database is a data module in which data is stored in the form of records and organized into a tree-like structure, or parent-child structure, in which on have many child nodes are connected through like. Example: IBM information management system (IMS).

Development of Database

The database has developed from a flat-file system to relational and object-relational systems throughout the span of over 50 years.

The primary systems to keep up with//maintain data were navigational databases, for example, the hierarchical database that used a tree-like design or structure, and the network database which used a relatively flexible model that allowed many relationships.

These early systems were inflexible, despite their simplicity. Relational databases acquired fame during the 1980s. After that object-situated databases acquired popularity during the 1990s.

NoSQL databases were grown or developed more recently in response to the expansion of the internet and more demand for faster processing of unstructured data.

These days, cloud databases and self-driving databases are being used for quicker handling or processing and cloud-based data storage.


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