SQL vs NoSQL : What’s the best option for your database?
One of the essential choices a developer must make is about what database technology to use for structuring and modelling data relationships.
For decades, SQL (Structured Query Language), the predominant data model language was used for application development by Oracle, SQL Server, MySQL, and PostgreSQL. On 2000s, some new data models began to gain significant adoption and usage. To differentiate these new classes of databases and data models, the term “NoSQL” was coined.
SQL Databases :
SQL Databases use structured query language (SQL) for defining and manipulating data. It is one of the most widely-used options available, making it a safe choice and especially great for complex queries.
You can use SQL when interacting with relational databases where data is stored in tables that have fixed columns and rows and must follow the same structure.
What is NoSQL database and how it works?
NoSQL (“non SQL” or “not only SQL”) database is a concept that was introduced in 1998 by Carl Strozz. It refers to any non-relational database that can store data in a format other than relational tables and uses a variety of data models for accessing and managing data.
NoSQL databases are purpose built for specific data models and fit many modern applications such as mobile, web and gaming as they have flexible schemas and are widely recognized for their ease of development, functionality, and performance at scale.
Amazon DynamoDB, ORACLE NoSQL, APACHE HBase and MongoDB are some of NoSQL non-relational database systems. Each system requires a little more technical expertise to understand and different syntax to work with.
What are the types of NoSQL Databases?
Over time, four major types of NoSQL databases have been emerged: document databases, key-value databases, wide-column stores, and graph databases. Let’s examine each of them:
· Document databases
Data is stored in documents. Each document contains pairs of fields and values. The values can typically be from different types (strings, numbers, booleans, arrays, or objects).
Thanks to their structures and powerful query languages, document databases are great for a wide variety of use cases and make it easier for developers to store and query data in a database by using the same document model format that they use in their application code.
· Key-value databases
are a simpler type of database where each item contains keys and values. A value can only be retrieved by referencing its key.
Key-value databases are great for use cases where you need to store large amounts of data but you don’t need to perform complex queries to retrieve it.
· Wide-column databases
store data in tables, rows, and dynamic columns. Wide-column stores provide a lot of flexibility over relational databases because each row is not required to have the same columns.
Wide-column stores are commonly used for storing Internet of Things data and user profile data.
· Graph databases
store data in nodes and edges. Nodes typically store information about people, places, and things while edges store information about the relationships between the nodes.
A graph database’s purpose is to make it easy to build and run applications that work with highly connected datasets. Typical use cases for a graph database include social networking, recommendation engines, etc …
SQL vs NoSQL: what should you opt for?
One of the main differences between these two types is that SQL databases are table-based databases and have a predefined schema whereas NoSQL databases use dynamic schema for unstructured data and can be stored either document based, key-value pairs, graph databases, etc … To decide which model to opt for you should know well the requirements of your project, scalability needs, how the data looks like before development begins ..
On one hand, SQL programming can be effectively used to insert, search, update, delete database records. This doesn’t mean SQL can’t do things beyond that. It can do a lot of things including analysing and getting data for further insights, optimizing and maintenance of databases. In addition to this, SQL databases are a better option for applications that require multi-row transactions and an ideal choice for the complex query intensive environments.
On the other hand, NoSQL doesn’t require a fixed schema. It avoids joins, and it is easy to scale. And as we said before, NoSQL database are great for modern applications and provides a great user experience. Thanks to its flexibility, scaling and high-performance, it is used for Big data and real-time web apps. For example, companies like Twitter, Facebook, Google that collect terabytes of user data every single day.
All in all, SQL or NoSQL data structure are both viable options to store your data, there are certain key differences between the two that you must keep in mind when making a decision.
