The big giants like Microsoft, Dell, Accenture, and Cognizant use SQL databases, while on the other hand, companies like Amazon, Adobe, Google, and Netflix use NoSQL. Now, you might be curious to understand the key differences between SQL and NoSQL. First, let's dive into the software world of understanding SQL and NoSQL from the absolute beginning.
What Is Structured Query Language (SQL)?
SQL is a programming language that differs from a general-purpose programming language such as Python, Java, and JavaScript. It has a specific purpose: to access and manage data in relational databases. It uses relations (referred to as tables) with a schema to manage and store data.
SOME OF THE RELATIONAL DATABASE EXAMPLES WHICH USE SQL ARE:
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Oracle
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Microsoft SQL server
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Ingres
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Microsoft office Access
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IBM DB2
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Sybase
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Google Cloud SQL
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Amazon RDS
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PostgreSQL
What Is Non-SQL Or Not Only SQL (NOSQL)?
It is a non-tabular and non-relational database with specific data models such as document, key-value, and graph formats to create modern applications. It is used for distributed data that requires a large stack of storage needs and can effectively store structured, unstructured, semi-structured, and polymorphic data.
SOME OF THE COMMON NOSQL DATABASE EXAMPLES ARE:
- MongoDB
- Couchbase
- Amazon's Dynamo DB
- CloudDB
- Apache's CouchDB
- MarkLogic
- Oracle NoSQL
- HBase
- Apache's Cassandra DB
- Redis
10 HEAD TO HEAD COMPARISONS OF SQL AND NOSQL
Comparison | SQL | NoSQL |
Key Purpose |
It can be used for data
|
It can be used for the maintenance and retrieval of different types of data
|
Schema | Rigid Schema (structured data) | Flexible Schema (unstructured data) |
Data Structure | SQL Data structures Table-based |
NoSQL Data structures
|
Scalability | Vertically scaled( add big servers) | Horizontally scaled(add more servers) |
Ideal use cases | It is well-suited for
|
It is well suited for
|
Hardware | Require powerful hardware to foster vertical scaling | Requires commodity hardware to foster horizontal scaling |
Database transactions | Follow ACID (atomicity, consistency, isolation, and durability) properties | Follow BASE (basic availability, soft-state, and eventual consistency) |
Architectural | Relational | Non-relational |
Key Features | Features of SQL
|
Features of NoSQL
|
Normalization & Joins | Normalization & joins are required | Denormalization & joins are not required |
After the astounding comparisons, let’s come to the SQL vs NoSQL pros and cons.
REALITY CHECK- SQL VS NOSQL PROS AND CONS
When looking for a data management system for your enterprises, you should consider the SQL vs NoSQL scalability, performance, schema, architecture, database transactions, and more.
Here is the SQL vs NoSQL pros and cons-
PROS OF SQL
1. Simplicity
The SQL databases have a simple structure that can be efficiently managed with simple SQL queries and doesn't require challenging architectural efforts.
2. Data security
Don't you think it is great to get high data security? Yes, it is possible with the SQL database because it stores the data in the form of tables which has restricted permission to confidential information.
3. Lowered data storage footprint
The lower data storage footprint is due to the optimization and normalization opportunities, resulting in enhanced database performance.
CONS OF SQL
1. Performance issues
When a large amount of data in a database and multiple users are logged in simultaneously, it might decrease the query response time.
2. Limited horizontal scalability
The SQL database can only be skilled vertically; hence it isn't easy to scale horizontally, slowing down the distributed database performance.
3. Cost factor
SQL database can include a high cost for its maintenance and development. In addition, it requires a team of experts to maintain it, which also inhibits an additional cost.
PROS OF NOSQL
1.High performance
NoSQL is generally built to deliver a high performance than SQL. Hence, some NoSQL databases provide impressive data processing speed.
2. Scalability
Did you know NoSQL databases are designed to handle large data sets? Therefore, they can be horizontally scaled to lodge more data requiring less maintaining low costs.
3. Flexibility
Thanks to the non-rigid structure of the NoSQL database, that can combine and store any type of data.
CONS OF NOSQL
1. Data analysis challenges
Most business and data scientists traditionally choose SQL due to its great data analysis potential, while with a NoSQL database, even the simplest queries need a certain level of expertise.
2. Lack of support
It doesn't have a vast community compared to SQL because it was introduced a few years ago. Therefore, it is unable to provide strong support, and it becomes difficult to resolve undocumented issues.
3. Issues with consistency
It shows consistency issues while handling a large amount of data and doesn't comprise with data redundancy mechanism. Hence, at the places where consistency issues can be acceptable, like shopping carts being updated and social media posts being alive, NoSQL can be used. Moreover, NoSQL is good in offering exceptional speed and availability rather than consistency.
Also Read: Monolithic vs Microservices Architecture
Who is the Real Winner-SQL or NoSQL?
When SQL and No SQL can be Used?
1. For a massively distributed system, consider using the Scylla, a distributed NoSQL wide-column store.
2. If the goal is a vertically scaled database, the go-to option will be an SQL database.
3. If the input data is relatively challenging to encapsulate and is heterogeneous, NoSQL is the best option.
4. Is ACID compliance your priority? Look no further than SQL databases.
5. If the temporary data needs to be stored like session data, wish lists, and shopping carts, you can choose NoSQL.
6. Do you wish to analyze behavioral-related and customized sessions? Prefer SQL database.
Final Thought: SQL VS NOSQL
The databases SQL and NoSQL have their own importance, and it profoundly depends on your business requirement and objectives. One of the biggest factors in understanding which database is the better choice depends on the type of data that needs to be stored. If you are still confused about which database to use.
Here is the heck:
SQL database is the preferred option if you are handling structured data that doesn't change much over time.
You can consider a NoSQL database if you handle a large chunk of data with little structure. If you are searching for the best software development company in USA that provides an efficient and streamlined database management solution for your enterprise, check out here.
Frequently Asked Questions
Qus. Why is SQL preferred over MongoDB?
SQL (Structured Query Language) and MongoDB are both popular database systems, each with its own strengths and weaknesses. While SQL is often preferred for its relational structure and powerful querying capabilities, MongoDB is better suited for unstructured data and rapid development.SQL's advantages include:
Relational structure: SQL databases store data in tables, which are interconnected through relationships. This makes it easier to manage complex data structures and perform complex queries.
Strong querying capabilities: SQL offers a rich set of query operators and functions for filtering, sorting, aggregating, and joining data. This makes it ideal for data analysis and reporting.
ACID compliance: SQL databases are typically ACID-compliant, ensuring data consistency and integrity.
However, SQL also has some drawbacks:
Schema rigidity: Once a schema is defined, it can be difficult to modify. This can limit flexibility and hinder rapid development.
Performance issues: SQL databases can become slow as the data volume grows, especially for complex queries.
Qus. Is it better to learn SQL or NoSQL?
The choice between SQL and NoSQL depends on your specific needs and preferences. If you are dealing with organized data and need robust search abilities, using SQL could be a suitable option. If you need to store unstructured data or prioritize rapid development, NoSQL may be a better option.Here are some factors to consider:
Data structure: If your data is highly structured, SQL is likely a better fit. If your data is unstructured or semi-structured, NoSQL may be more suitable.
Query complexity: If you need to perform complex queries, SQL offers a richer set of features.
Development speed: NoSQL databases can often be easier to develop with, especially for simple applications.
Scalability: Both SQL and NoSQL databases can be scaled to handle large datasets, but the specific mechanisms may differ.
Qus. Which is in demand: SQL or NoSQL?
Both SQL and NoSQL are in high demand in the job market. However, SQL is still the more widely used database technology, particularly in traditional enterprise applications. NoSQL databases have gained popularity in recent years, especially for web and mobile applications.Qus. Should I learn SQL or MongoDB first?
If you are new to databases, it is generally recommended to start with SQL. SQL is a fundamental technology that is widely used in the industry. After gaining a strong grasp of SQL, you can then acquire knowledge of NoSQL if necessary.However, if you are primarily interested in developing web or mobile applications, you may want to start with MongoDB. MongoDB is often used in these types of applications, and it can be easier to learn if you are already familiar with JavaScript.