Our Blogs

Introduction:

When it comes to choosing the correct database for one application, the biggest of the decisions is which one to choose: relational (SQL) or non-relational (NoSQL). While both of the databases are viable options, there are certain key differences between them that the users must keep in mind. SQL is a decades-old method for accessing relational databases, and most users working with databases are familiar with it. But as unstructured data, amounts of storage and processing power, and types of analytics increased and changed over the years, we have seen different types of databases become available that fit the newer use cases. These databases are commonly called NoSQL.

What is SQL?

Structured Query Language (commonly known as SQL) is a domain-specific language used in designing and programming for managing data stored in a relational database management system (or RDBMS) format or for stream processing in a relational data stream management system (or RDSMS). It offers fast data storage and recovery and can handle great amounts of data and complex SQL queries. It introduced the concept of accessing many records with a single command. It is particularly useful in handling structured data, i.e. data incorporating relations among entities and variables.

What is NoSQL?

NoSQL (also referred to as non-SQL or non-relational) databases provide a mechanism for storing and retrieving data in other ways than the tabular relations used in relational databases. Motivations for this approach include simplicity of design, simpler "horizontal" scaling to clusters of machines (which is a problem for relational databases), finer control over the availability, and limiting the object-relational impedance mismatch. The data structures used by NoSQL databases (e.g., key–value pair, wide column, graph, or document) are different from those used by default in relational databases, making some operations faster in NoSQL. The particular suitability of a given NoSQL database depends on the problem it must solve.

Differences to keep in mind:

Type: SQL databases are primarily relational databases, whereas NoSQL databases are primarily non-relational databases or distributed databases.

Language: SQL databases define and manipulate data based on a specific language, commonly known as "structured query language." Looking at it from one perspective, it seems to be extremely powerful. It is one of the most versatile and widely-used options available, which makes it a more prominent choice for complex queries. But from another perspective, it seems to be much more restrictive. It requires predefined schemas to determine the structure of the users’ data before one can work with it. Also, all the data must follow the same structure. This requires a significant amount of up-front preparation, which creates a problem if the data structure needs to be changed, as it would be both difficult and disruptive for the whole system. A NoSQL database provides us with a dynamic schema for unstructured data. Data here is stored in many different ways. This flexibility provides the benefit of not having to predefine anything, and one can also store different types of unstructured data in the same storage area. Also, each document has its unique structure, though the syntax varies from database to database and one can keep on adding fields as they proceed.

Scalability:- In almost all situations, SQL databases are vertically scalable. But on the other hand, NoSQL databases are horizontally scalable. This means that you handle more traffic by sharding or adding more servers in your NoSQL database. Thus, NoSQL can ultimately become larger and more powerful, making these databases the preferred choice for large or ever-changing data sets.

Structure:- SQL databases are table-based on the other hand NoSQL databases are either key-value pairs, document-based, graph databases, or wide-column stores. This makes relational SQL databases a better option for applications that require multi-row transactions such as an accounting system or for legacy systems that were built for a relational structure.

Property followed:- SQL databases follow ACID properties (Atomicity, Consistency, Isolation, and Durability) whereas the NoSQL database follows the Brewers CAP theorem (Consistency, availability, and Partition tolerance).

Support: Great support is available for all SQL databases from each of their vendors. A lot of independent vendors are available who can assist with various large-scale deployments. Whereas for some NoSQL databases, one has to still rely on community support, and only a limited number of outside experts are available for setting up and deploying large-scale deployments.

Examples:

SQL Database:- Oracle, MySql, Postgres, etc

NoSQL Database:- MongoDb, Neo4j, Apache Cassandra, etc.