NoSQL vs SQL? How to Choose the Best Fit for a Project
Data persistence has always been a key challenge faced by software developers and programmers.
Several database management systems have been created in order to handle data persistence issues in software products.
For decades, SQL-based relational database management systems (RDBMS) dominated the IT world.
But with the explosion of new data sources and types, developers now often face an important choice—choosing between SQL and NoSQL for their applications.
This article will help you understand the key differences between SQL and NoSQL and guide you in selecting the best fit for your project.
What Are SQL and NoSQL Databases?
Before getting into detailed comparisons, it’s important to understand the basic idea behind SQL and NoSQL databases.
SQL databases are relational databases that store data in structured tables. Each table has a predefined schema, which defines the structure of data (such as types of fields and relationships between tables). Data retrieval and management are done using Structured Query Language (SQL). Examples include MySQL, PostgreSQL, and Oracle Database.
NoSQL databases are non-relational databases that store data in flexible formats like documents, key-value pairs, graphs, or wide-columns. They do not require a fixed schema, making them suitable for applications where data structure can evolve over time. Examples include MongoDB, Cassandra, and Redis.
Why NoSQL Databases Were Created
SQL-based relational database management systems (RDBMS) are highly structured. Data is stored in the form of well-organized tables with associations among them. This data is queried using a structured query language.
There are, however, certain limitations to this approach. Modern systems often have to handle enormous amounts of data, or Big Data, coming from different sources. Conventional SQL-based RDBMS often struggle with Big Data.
To combat this, NoSQL database management systems were introduced.
Factors Affecting the NoSQL vs SQL Decision
When deciding between a SQL or NoSQL database for a particular project, the following considerations should be taken into account.
1. Type of Data
Choosing a database depends mainly on the type of data that your project needs to store. If your data is highly structured and associations among the program entities are clearly defined (for instance, you are developing a point-of-sale system where you need to store customer orders and product records), conventional SQL-based databases are the best fit.
On the flip side, data from molecular modeling, Geo-spatial information, and satellite data is highly unstructured. Likewise, data from social media analysis and websites is also highly unstructured, and relationships among the data entities are not clearly defined. In such scenarios, NoSQL is a better choice. For example, a data mining application should utilize the power of the best NoSQL database rather than conventional SQL.
Before deciding what is better, SQL or NoSQL? It is important to evaluate the nature and structure of your project’s data carefully.
2. Database Volatility
Software development is an Agile process where requirements can quickly change, which affects the database schema as well. It is almost impossible to correctly implement the database schema in the first shot. If persistent data of the project is more likely to change in the future, NoSQL databases are a better option. Because they don’t have a rigid scheme, they are more suitable for such projects.
3. Time and Cost
Time is crucial in the software development life cycle. In the past, companies hired dedicated database administrators, while software developers mainly focused on application development aspects. However, this decoupling of DBA and software developers increased software development time and cost.
The best NoSQL database technologies allow software developers to integrate data and development perspectives, leading to cost-effective and timely delivery of software projects.
4. Scalability
Scalability is a significant issue with SQL-based databases. With the huge magnitude of information needed to be stored, data size grows exponentially. SQL-based databases undergo vertical scaling, which is extremely costly.
On the other hand, NoSQL DBs scale horizontally and scalability issues can easily be handled by adding another node in a database cluster. Google’s HDFS scaling systems is one example.
When comparing NoSQLvs SQL, horizontal scaling gives NoSQL databases a major advantage in handling Big Data cost-effectively.
5. Data Mining and Machine Learning Perspective
Data mining and machine learning are processes of analyzing data in order to extract useful information and patterns that can be used in decision-making processes. These techniques are usually applied over enormous and extremely versatile data. Therefore, in such projects, NoSQL databases are a better choice.
Popular SQL and NoSQL Database Examples
Choosing the right database involves understanding the available options. Here are some of the most widely used SQL and NoSQL databases:
Popular SQL Databases:
MySQL: An open-source relational database known for its reliability and ease of use.
PostgreSQL: A powerful open-source SQL database with strong support for advanced data types and performance optimization.
Microsoft SQL Server: A widely adopted relational database management system for enterprise-level applications.
Oracle Database: A commercial SQL database solution often used for large-scale, mission-critical systems.
Popular NoSQL Databases:
MongoDB: A document-oriented database known for its scalability and flexibility.
Cassandra: A wide-column store designed for handling large amounts of data across multiple servers with no single point of failure.
Redis: A key-value store often used for caching and real-time analytics.
Couchbase: A document store database designed for high availability and performance at scale.
Familiarity with these tools can help you choose between SQL and NoSQL for your project, depending on factors like scalability, performance, and data structure needs.
SQL or NoSQL Database: Which Should You Choose?
When making the NoSQL vs SQL decision, the needs of the project should be your guiding light. If the project is expected to see drastic changes, needs to handle a huge and versatile amount of data, or the database entities and schema are ambiguous at the start, go for the best NoSQL database you can afford.
However, if the project needs to handle small and homogeneous data, and the database entities are clearly defined with unambiguous relationships (which rarely is the case), SQL is a good fit.
