What database types exist?

There are two types of modern databases: relational and non-relational. However, database implementations can vary significantly based on what specific use-cases they are designed to cater to and what technology vendor is distributing it. In this shot, we will go over the two overarching types.

Relational Databases

Relational Database Management System (RDBMS) are called this because data is stored in schemasThe database schema describes the relation of one table to another in formal language. that relate information together (i.e., relates one table to another). You typically query RDBMS using Structured Query Language (SQL).

SQL is the query language used for relational databases; SQL may be used for non-relational databases, but its execution is very different from the way a traditional RDBMS would manage it. Read about the differences in relational and non-relational databases in our shot on SQL and NoSQL.

Non-relational databases

Non-relational or NoSQL databases have only recently matured as an alternative to traditional RDBMS. NoSQL is much more flexible in the sort of data that is allowed, which might make them more suitable for web-based data. There are multiple implementations of NoSQL.

Types

The following is a collection of prominent approaches:

Key-Value Stores are simple implementations meant to provide speedy transactions. These databases only store key-value pairs and provide basic functionality for retrieving the value from a given key.

Wide Column Stores are designed with the intention to scale data across thousands of servers in a large, distributed system. Wide column stores can be thought of as multi-dimensional key-value stores.

Document Stores are similar to key-value stores. Typically, the name of the document is the key and the content of the document is the value in the form of JSON documents.

Graph Databases represent data as a network of related nodes or objects in order to facilitate data visualization and analytics. Graph-based DBMS are developed to better illustrate the connections between data, which makes then ideal for analysis.