SQL vs. NoSQL

A database is a collection of data where it is typically designed so that it is easy to store and access information. A good database and database management system is crucial to any company or organization. Since the database stores all the essential and sensitive details about  the company such as employee records, transactional records.

When it comes to choosing a database, people generally choose between a relational (SQL) or non-relational (NoSQL) data structure. Both the databases have their pros and cons, so it is important for the users to understand the certain key differences between the two.

Introducing SQL

SQL databases are also known as Relational Databases (RDBMS). SQL databases define and manipulate data based structured query language (SQL). SQL is powerful in the sense that it is one of the most versatile and widely-used options available which makes it a safe choice especially for executing a lot of complex queries. But from the other side it can be restrictive. SQL requires you to use predefined schemas to determine the structure of your data before you work with it. This can require significant up-front preparation which means that a change in the structure would be both difficult and disruptive to the entire system.

Introducing NoSQL

NoSQL databases are also known as non-relational or distributed databases. A NoSQL database has dynamic schema for unstructured data. Data is stored in many ways which means it can be document-oriented, column-oriented, or graph-based. This means that documents can be created without having defined structure first and having that flexibility can be a potential advantage for the users. The syntax varies from database to database, and you can add fields as you go.

Data Query

A factor to consider is how often you or your company will query the data, the speed that needs to  run queries, and who will be responsible for running these queries. If the data is structured and organized, it is very efficient to query the data with a SQL database. SQL will efficiently execute queries, retrieve and edit data quickly. Since SQL is very lightweight and declarative, it becomes easier for less technical staff like business analysts and marketers to pick up and apply.

A NoSQL database provides a ton of flexibility in the types of data that can be stored, but due to the large differences in data structures, querying is not as efficient as with a SQL database. In order to run NoSQL queries, you will have to perform extra processing on the data. In contrast to SQL databases, querying in NoSQL databases typically requires developers or data scientists to analyze.

Scalability

SQL and NoSQL databases scale differently, so users will have to think about how the data set will grow  and scale in the future.

SQL databases scale vertically, meaning you might need to increase the capacity of a single server to scale your database. SQL databases were designed to run on a single server to maintain the integrity of the data, so they are not easy to scale.

Compared to SQL databases, NoSQL databases scale horizontally, meaning you can add more servers to power your growing database. This is a huge advantage that NoSQL has over SQL. The ability of NoSQL databases to horizontally scale has to do with the lack of structure of the data. Since NoSQL requires much less structure than SQL, each stored object is self-contained and independent.

Functionality Comparison Chart  

SQL

NoSQL

Fixed or static or predefined schema

Dynamic schema

Not suited for hierarchical data storage

Best suited for hierarchical data storage

Best suited for complex queries

Not so good for complex queries

Vertically Scalable

Horizontally scalable

Manage Your SQL and NoSQL Databases

SQL and NoSQL databases can be used for different types of data. A business may use two types of databases at the same time. However, you have to use different ways to retrieve data from two database systems. (For example, you can write SQL queries to get data from SQL databases, but SQL cannot work on NoSQL databases). In addition, two database systems cannot talk to each other. If you want to consolidate and analyze data from two systems, you have to export data from two systems and start your analysis.

One way to solve this problem is to use cloud database management platforms. Cloud database management platforms such as Acho can connect to various data sources.

Acho Data Source Import Page

Take Acho as an example. Acho allow you to connect to SQL and NoSQL databases at the same time and convert data into a structured format. Thus, even if data is from NoSQL database, it will be displayed in a tabular format instead of a JSON format. In addition, you can view and compare data from both SQL and NoSQL databases. Even, you can write SQL to query data from two systems. If you are not familiar with SQL, you can use built-in ”actions”, such as Filter, Join, or Sort. These actions transform complex SQL queries into intuitive buttons, so you can use them to deal with your data easily.

Now with the introduction of different methods of database management, whether you are using SQL, NoSQL, or other services, ensure that you understand the constraints and functionalities that each can provide.