Relational vs Non-Relational database
Relational vs Non-Relational database
You’ve probably come across the term database at some point in
your life. Database is a set of data that is stored on a computer.
Hospitals use databases to track the treatments they administer;
accountancy firms use databases to keep track of accounting records and web
applications use databases to keep a list of their users and the content of
their platform.
So lets start with simple question..
What is a Database?
A database is an organized collection of
structured information, or data, typically stored electronically in a computer
system. A database is usually controlled by a database management system (DBMS). Together, the data and the DBMS, along with the applications that are
associated with them, are referred to as a database system, often shortened to
just database. Within each table you can keep a record of the names entered one by one
on your website. Each value in the record must match the columns in the table.
There are two main types of databases used in database management system i.e. relational and non-relational. The main difference between the two is a type of used structure.
· Relational
databases use tables and that are all connected to each other.
· Non-relational
databases, on the other hand, are document-oriented. Unlike tables, which are
responsible for a single type of data, they can store information under
different categories, which all depend on different commands.
What is a relational database?
A
relational database, or relational database management system (RDMS), stores
information in tables. Typically, these tables have shared information between
them, causing a relationship to form between tables. This is where a relational
database gets its name from.
A
table uses columns to define stored information and rows for the actual data.
Each table will have a column that must have unique values—known as the primary key. This column may
be used in other tables, if relationships are to be defined between them. When
one table’s primary key is
used in another table, this column in the second table is known as the foreign key.
The
most common way of interacting with relational database systems is using SQL
(Structured Query Language). Developers can write SQL queries to perform CRUD
(Create, Read, Update, Delete) operations.
Imagine
you run an online business. You have a variety of information that you store,
like customer information, order information, and products. In a relational
database, this would be stored in different tables with a key to join the
tables when needed.
Here, is the customer table
stores the basic customer information, order id and address id. If
someone needs more information on the order or address, they can query the
matching order and address tables
using an INNER JOIN operator with the id field. The order table
in turn has product ids of the product items in the order. The details of the
product are in a separate product table. This makes information organized and
more structured.
What is a non-relational database?
A
non-relational database, sometimes called NoSQL (Not Only SQL), is
any kind of database that doesn’t use the tables, fields, and columns
structured data concept from relational databases. Non-relational databases
have been designed with the cloud in mind, making them great at horizontal scaling.
There are four
different types of NoSQL databases.
- Document-oriented
databases –
Also known as a document store, this database is designed for storing,
retrieving and managing document-oriented information. Document databases
usually pair each key with a complex data structure (called a document).
- Key-Value
Stores –
This is a database that uses different keys where each key is associated
with only one value in a collection. Think of it as a dictionary. This is
one of the simplest database types among NoSQL databases.
- Wide-Column
Stores –
this database uses tables, rows, and columns, but unlike a relational
database, the names and format of the columns can vary from row to row in
the same table.
- Graph
Stores –
A graph database uses graph structures for semantic queries with nodes,
edges, and properties to represent and store data.
Non-relational
databases are becoming more popular as more and more businesses begin to
leverage big data for analysis and reporting. Since critical data doesn’t
always fit well into a pre-defined schema, NoSQL databases allow more
flexibility.
When to use a relational database?
If
you’re creating a project where the data is predictable, in terms of structure,
size, and frequency of access, relational databases are still the best choice.
Normalization
can help reduce the size of the data on disk by limiting duplicate data and
anomalies, decreasing the risk of requiring vertical scaling in future.
Relational
databases are also the best choice if relationships between entities are important.
Non-relational
databases can store documents within the documents, which helps keep data that
will be accessed together in the same place. But if this isn’t right for your
needs, a relational database is still the answer. For example, if you have a
large dataset with complex structure and relationships, embedding might not
create clear enough relationships.
The
amount of time that RDMSs have been around also means there is wide support
available, from tools to integration with data from other systems.
When to use a non-relational database?
As
discussed, there are many types of non-relational databases, each having their
own advantages and disadvantages.
However,
non-relational databases still maintain some consistent advantages. If the
data you are storing needs to be flexible in terms of shape or size, or if it
needs to be open to change in future, then a non-relational database is the
answer.
Modern
NoSQL databases have been designed for the cloud, making them naturally good
for horizontal scaling where a lot of smaller servers can be spun up to handle
increased load.
Why might you prefer a
non-relational database over a relational database?
There
are many reasons why you’d want to use a non-relational database over
a relational database:
- Non-relational databases are
suitable for both operational and transactional data.
- They are more suitable for
unstructured big data.
- Non-relational databases offer
higher performance and availability.
- Flexible schema help non-relational
databases store more data of varied types that can be changed without
major schema changes.
Summary
In
this article, you have learned about relational vs non-relational databases and
how they differ from each other. You’ve also learned the advantages and
disadvantages of both types of databases and which database type is most
suitable for various projects.
|
Features |
Non-Relational |
Relational |
|
Availability |
High |
High |
|
Horizontal Scaling |
High |
Low |
|
Vertical Scaling |
High |
High |
|
Data Storage |
Optimized for huge data volumes |
Medium to large
data |
|
Performance |
High |
Low to Medium |
|
Reliability |
Medium |
High |
|
Complexity |
Low |
Medium |
|
Flexibility |
High |
Low |
|
Suitability |
Suitable For OLAP and OLTP |
Suitable For OLTP |
MongoDB is a non-relational database that
offers scalability, high performance, reliability, and flexibility. MongoDB has
grown into a wider data platform with MongoDB Atlas,
MongoDB’s cloud-based database, which makes data available at all times.
Very helpful 👍🏻👍🏻
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