With novel introductions in database management systems, it is difficult for enterprises and individuals to decide what to choose. Having a traditional SQL data store and a newly popular DBMS known as NoSQL, understanding the substantial difference between SQL and NoSQL can only help us choose the right database for our business and software development applications.
Check this video On NoSQL vs SQL:
What is SQL?
Structured Query Language or SQL is a standard database language used to create, maintain, and retrieve the relational database. Some of the key features of SQL that make it a popular database management system of all times are:-
- They fit into most of the popular software stacks
- The easy and familiar structure makes it a preferred option
- Eliminates redundancy and synchronizes the data
However, these benefits may not be sufficient for changing business scenarios. This gap is filled by NoSQL.
What is NoSQL?
Many of us only know about SQL to be the oldest DBs we have, and it would be surprising for you to know that NoSQL existed before SQL’s usage exploded in the 1990s. NoSQL is as old as the 1960’s. However, they have gained popularity lately with the eruption of several options like MongoDB, Cassandra, and HBase.
NoSQL databases are non-tabular databases and store data differently than relational tables.
NoSQL vs. SQL: Key Differences
Till now you must have gotten a clear picture of both the databases, however, a brief comparison will give a clearer view –
| Parameters | NoSQL | SQL |
| Definition | Called as Non-relational database | Called as Relational database |
| Schema | Dynamic schema | Static schema |
| Representation | Represented as key-value pair, graph database, wide-column stores, etc. | Represented as tables |
| Scalability | Horizontally scalable | Vertically scalable |
| Complex Queries | Not so good for complex queries | Best for complex queries |
| Language | Language varies from database to database | Uses a powerful standard language called “Structured Query Language” (SQL) |
| Type | Table-based databases | Document based, key-value pairs, graph databases |
| Hierarchical data storage | Not suitable for hierarchical data storage | More suitable for the hierarchical data store as it supports key-value pair method |
| Variations | One type with minor variations | Multiple types which include document databases, key-value stores, and graph databases |
| Open-source | A mix of open-source and commercial | Open-source |
| Consistency | Needs to be configured for strong consistency | It depends on DBMS as some offer strong consistency whereas others only offer eventual consistency, like Cassandra |
| Best Used for | For solving ACID problems | For solving data availability problems |
| Importance | Used when data validity is preferred | Used when fast data is preferred than correct data |
| Best Option | For supporting dynamic queries | For scaling as per changing requirements |
| Hardware | Specialized DB hardware like Oracle Exadata | Commodity hardware |
| Network | Highly available network (Infiniband, Fabric Path, etc.) | Commodity network (Ethernet, etc.) |
| Storage Type | Highly available storage (SAN, RAID, etc.) | Commodity drives storage (standard HDDs, JBOD) |
| Best Features | Cross-platform support, free, and secure | High performance, easy-to-use, and flexible tool |
Advantages and Disadvantages of NoSQL
Some of the distinctive NoSQL advantages and disadvantages are explained below –
Advantages:
- There is no constraint on the structure of the data to be stored
- Integration with cloud computing gives it an edge
- The dynamic and quick development of a database is possible
- Huge amounts of data can be stored
Disadvantages:
- Not all NoSQL databases contemplate the atomicity of instructions and the integrity of the data and they withstand eventual consistency
- There are compatibility issues with SQL instructions as new databases are not yet entirely compatible with the SQL used in relational databases
- There are many NoSQL databases and there is still no standard like the ones that exist in relational databases
- Improvements are yet to be made for cross-platform support
Learn these NoSQL Interview Questions asked by top MNCs!
Advantages and Disadvantages of SQL
Advantages:
- Large amounts of data are retrieved quickly and efficiently, and operations are executed in no time
- Large lines of code are not necessary for data retrieval, and the syntactical rules are not complex making it a user-friendly language
- Provides a uniform platform worldwide owing to the available documentation and long period of establishment
- It can be used in programs on servers, PCs, and laptops independent of any platform and can be embedded with other applications making it really portable
- It is an interactive language that is easy to learn and understand
- Multiple data views are possible in SQL
Disadvantages:
- SQL has a difficult interface that can be uncomfortable for users dealing with the database
- Some versions of SQL are costly making it inaccessible to programmers
- Due to hidden business rules, only partial control is given to the database
Is NoSQL better than SQL- Truth or myth?
The choice between SQL and NoSQL does not depend on the advantages and disadvantages of these database systems, rather it’s the type of web applications you deal with and the results you expect from a query system.
Whenever people compare SQL with NoSQL, they state that NoSQL overpowers SQL and is better. You must know that this is MYTH! Remember, none of them supersedes each other and NoSQL is not a replacement for SQL but rather an alternative to it.
In reference to the differences, one of the technology experts said, “One size does not fit all.” It means some projects and applications are better suited on SQL while others are on NoSQL.
In fact, some SQL databases are adopting features of NoSQL and working in collaboration. There has always been some kind of rules while using databases like only MySQL (SQL) databases being used by PHP or .Net projects. Do not consider it a rule; you may use MongoDB (NoSQL) in your PHP application. Similarly, you can use SQL Server in Node.js applications, instead of considering NoSQL as the only suitable fit.
Prepare yourself for the industry by going through these Top MySQL Interview Questions and Answers!
SQL Tables vs. NoSQL Documents
| Course Code | Title | | Company | Training Format | Price (in $) |
| 7654389 | Tableau Training | | Intellipaat | Online | 150 |
| 3456789 | Big Data Training | | IBM | Online | 200 |
SQL provides a storage database in the form of a relational table model, i.e., rows and columns. For instance, you have a table named training_course with the above-mentioned data of two online training companies. Each row has a different record. In this table, the data type of each field is fixed and you cannot insert a number in place of a string.
On the other hand, NoSQL databases make use of field-value pairs in a document, similar to JSON.
For instance,
{
Course Code: 7654389
Title: “Tableau Training”,
Company: “Intellipaat”,
Training format: “Online”,
Price (in $): 150
}
Such documents are stored in a collection in NoSQL database as they are stored in a table in SQL. But, you can store any type of data you wish in any of the documents of NoSQL.
{
Course Code: 7654389
Title: “Tableau Training”,
Company: “Intellipaat”,
Training format: “Online”,
Price (in $): 150,
Rating: 5/5
Review:
[
{ name: “Alex” , text: “The course was very helpful in preparing for Tableau Certification.” },
]
}
Unlike SQL database, which is strict to allow any changes in data type and has a fixed data template, NoSQL employs more flexibility. However, sometimes a lot of changes lead to consistency issues.
Now, we will talk about the two most important criteria that will decide your selection- Schema structure and Data Integrity. Read below-
SQL has a Schema structure while NoSQL is schema-less
The tables in the SQL database refer to the schema structure, which contains information about the following parameters:
Primary key: A unique field that can help you identify a record uniquely; for instance, Course Code in the above table
Relationship: Refers to logical links between two and more data fields in a table. Functionality like Triggers, Views, Stored Procedures, Joins, etc.
Most SQL Developers decide and define the schema structure including any of these functionalities in their table before implementing or applying any business logic to modify and/or update the table. This is because it becomes complex to make significant changes later.
On the contrary, as mentioned, NoSQL is formative and the data can be modified and added anywhere at any time. You need not mention a predefined document design. In MongoDB,
db.table_course.insert command lets you create a new document if it wasn’t created before. It will by default add a unique _id to every document present in a collection.
Check out the difference between SQL and MySQL in our comparison blog on SQL vs MySQL.
Data Integrity: An Important criterion
As you know while working with two SQL tables, you can relate them with a foreign key field. This refers to data integrity. If we have a project table, the project_id will be the foreign key and the rules could be defined as:
- It should be ensured that each training course should have a project_id matching that in the project table.
- Do not let users delete projects if there are one or two training courses assigned to them
In this case, it is complex for Developers and Database Administrators to edit or delete records, resulting in inconsistent databases. There is no data integrity operation available with NoSQL databases. Each document acts as an independent source of information about an item.
Conclusion
Ultimately, the choice between SQL and NoSQL databases cannot be concluded based on the differences between them but on the project requirements. If your application has a fixed structure and doesn’t need frequent modifications, SQL is a preferable database.
Conversely, if you have applications where data is changing frequently and growing rapidly like in Big Data Analytics, NoSQL is the best option. SQL is still a widely used database and will not easily die out even with the introduction of other database technology.
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