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Non-Relational Databases and Their Types

Last Updated : 20 May, 2024
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Non-relational databases store data in non-tabular format, unlike relational databases that store data in tables in the form of rows and columns. They are also known as No-SQL databases.

Unlike traditional relational databases(SQL), they do not depend on a fixed schema, allowing for easier handling of unstructured data. Non-relational databases are ideal for handling large volumes of data and are highly efficient in distributed environments.

Here, we will learn about non-relational database meaning and check non-relational database examples. But to understand non-relational databases, or “NoSQL” databases, we first need to look at relational databases.

Relational Database (SQL)

A relational database stores data in a table composed of rows and columns. The table represents an object or entity, such as users, customers, orders, etc.

The column represents the type of data that can be stored in the respective column. Relational Databases allow users to establish a connection between tables using keys for flexible data flow and querying.

SQL was specifically designed to work with tabular data. These are often categorized as structured data. This is because there can only be a single schema or structure for the data within a relational database. SQL is a declarative language, which means that you describe in SQL syntax the desired result you wish from the query.

Key features of relational database

Key Features of Relational Databases

Key Features of Relational Databases

  • Relational data models are similar to an Excel spreadsheet, with related data stored in rows and columns in one table.
  • SQL (Structured Query Language) is the most common way of interacting with relational database systems. Developers can write SQL queries to perform CRUD (create, read, update, delete) operations.

Non-Relational database (NoSQL)

Non-relational databases different from relational databases because they do not store data in tabular form. Instead, non-relational databases are based on data structures like documents and graphs. No-SQL databases also come in a variety of types based on their data models.

They offer scalability when dealing with large volumes of data and high load factors. They were designed when data was expected to be partitioned across multiple machines to scale, in contrast to relational databases, which assumed the data would stay on a single machine.

Non-Relational Database Types

There are four main types of non-relational databases:

  • key/value
  • graph
  • column
  • document
Non Relational Databases

Non Relational Databases

1. Key/Value Database

Key/ Value Database

Key/ Value Database

Key-value databases use a straightforward schema: a unique key is paired with a collection of values, where the values can be anything from a string to a large binary object. One of the benefits of using this structure in a database is that you don’t have to worry about complex queries. Because the system knows where the data is stored, it only sends a request to that particular server.

Key/Value Database Example:

Key

Value

Name

John Snow

Age

23

2. Graph Database

Graph Database

Graph Database

Graph database is another type of non-relational database. A popular example of a graph database is Neo4J. This database stores information as a collection of nodes and edges, where the edges represent the relationships between the nodes.

3. Column Oriented Database

Wide Column

Wide Column

A column-oriented or wide-column non-relational database is primarily designed for analytics. Cassandra is a commonly used column-oriented database.

The advantage of column-oriented/row-oriented databases is that column-oriented databases return data in columns, making the query much more performant as it will not return many irrelevant fields that are not required for the query being serviced.

The primary key in a column-oriented database is the data or value, which is then mapped to row keys. This is the inverse, or opposite, of how the primary key works in a relational database.

Column Oriented Database Example:

Example of Column Oriented

4. Document Database

Document Database

Document databases, such as MongoDB, store data in a single document, which can have different shapes within the single collection or table that stores the documents. It provides a clear means of capturing relationships using sub-documents and embedded arrays within a single document.

Document Database Example

Document Database Example

Non-Relational Database Management Systems

Some of the popular Non-Relational Database Management Systems are:

  1. MongoDB
  2. Apache Cassandra
  3. Redis
  4. Couchbase
  5. Apache HBase
  6. Neo4j
  7. Riak
  8. Aerospike
  9. OrientDB
  10. ArangoDB

These are some Non-relational database names, that you might hear in the market. Decide on which Non-relational database software is best for your work, and master that.

Relational vs Non-Relational Database

The below table shows the difference between Relational and Non-Relational Databases.

Aspect Relational Database (SQL) Non-Relational Database (NoSQL)
Data model Tabular Key-value, document, wide-column, and graph
Schema Requires a predefined schema with a fixed structure Typically schema-less or flexible schema allowing varied data structures within the same database
Scalability Primarily scales vertically, requiring more powerful hardware for scaling Designed for horizontal scalability, can easily scale out by adding more nodes
Query language Uses structured query language (SQL) for defining and manipulating data No standard query language. Query methods vary based on the type of NoSQL database
Data integrity Strong focus on data integrity with ACID compliance Typically eventual consistency. Focus on availability and partition tolerance (CAP theorem)
Flexibility Less flexible; schema changes can be complex and disruptive Highly flexible in terms of data models and schema changes
Use cases Well-suited for structured data with clear relationships, requiring complex queries and high data integrity Ideal for unstructured data, real-time applications, big data analytics, and rapidly evolving data requirements

Conclusion

In conclusion,  non-relational databases offer a flexible and scalable solution for managing large volumes of unstructured data. They are particularly useful for applications that require high performance and low latency. There are four main types of non-relational databases: key-value, document, column oriented, and graph database.



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