The need for a No-SQL database skyrocketed when the conventional database could not handle the unstructured and varying schema data. In this blog, we will make a detailed comparison between MongoDB vs SQL and understand why we should choose one over another.
What is MongoDB
Mongodb is one of the most popular open-source, No-SQL databases.MongoDB is non-relational and can have a dynamic schema that enables users to insert the data into MongoDB without defining the schema.
In MongoDB, users have the flexibility to define the schema to force users to insert data having particular fields. It can handle operational, transactional, and analytical workloads easily.
MongoDB uses the BSON format to represent the data and is easily scalable as per one’s requirements. You can interact with MongoDB either by command line or using an atlas.
Mongodb also has an enterprise version, which provides more features and enterprise support than the open-source mongoDB version.
What is SQL
SQL stands for Structured Query Language. SQL databases are mainly used to store the structure data. Structure data means data with a defined number of rows and columns. The data in SQL databases gets stored in tabular format.
Some of the popular SQL databases are:-
- Microsoft SQL Server
Most such SQL databases are free and open-source. These databases are easy to set up and give high throughput while querying data.
You can check the below link to compare the two most popular SQL databases with MongoDB.
MongoDB vs SQL Features
Please follow this link to learn about the features of mongodb.
The Important features of SQL are as follows:
- SQL databases can be easily scalable.
- Most of the SQL databases have a replication feature using which we can easily replicate the data to multiple servers.
- SQL databases follow SQL query language.
- All SQL databases follow joins.
MongoDB vs SQL pros and cons
Pros of MongoDB
Please follow this link to learn about the pros of Mongodb.
Pros of SQL
ThePros of SQL are as follows:
- Faster query: Using SQL queries, users can easily and effectively query large amounts of data.
- No coding required: All SQL database follows standard SQL commands, which are relatively easy to learn and implement.
- Open source: Most SQL databases are open source which means users can install and use them without paying a single penny.
- Portable: Users can write the SQL queries on their mac, tablet, smartphone, and on SQL databases installed on macOS, Windows, Linux, and Unix environments, and the query will behave the same irrespective of the environment. So we can quickly move the queries from one environment to another.
- Easy to learn: The SQL language is relatively easy to understand, and within a few days of practice, users can able to write complex queries
- Widely used: Almost all companies use SQL databases to store data of their front-end application or store other applications’ metadata.
Cons of MongoDB
Please follow this link to learn about the cons of Mongodb.
Cons of SQL
TheCons ofSQL are as follows:
- The developer doesn’t have complete control over the SQL because there are few hidden business rules implemented by default in SQL.
- SQL has a difficult interface which makes some users uncomfortable while interacting with SQL.
- Though most SQL databases are open source, you need to purchase the enterprise’s product if you need to have advanced features.
- Some SQL database follows their SQL language derived from standard SQL to force the enterprise to use their version of SQL.
MongoDB vs SQL
This session will see the difference between MongoDB and SQL on various parameters.
Mongodb vs SQL general differences
This session will explore the general difference betweenMongodb and SQL databases.
|MongoDB is a non-relational database||SQL databases are relational|
|In Mongodb, data is saved as a JSON document.||In SQL, data is saved in a table in rows and columns|
|Developed in the year 2000||Developed in the year 1970|
|It does not support SQL language||Supports SQL language|
|Users can insert data into mongodb with varying schema||Supports data with a fixed number of columns|
|Does not supportforeign key||Support foreign key|
|It does not support joins||Support joins|
|No support for triggers||Support for triggers|
|MongoDB supports horizontal scaling, which means we can quickly scale by adding more servers.||Most of SQL databases support vertical scaling(adding more resources)|
|NO support for ACID properties||Support ACID properties|
|No need to define a schema before inserting a record into mongodb||The user needs to determine the schema of a table before inserting a record in SQL databases|
MongoDB vs SQL scalability
When it comes to scaling on databases, MongoDB has the edge over SQL databases because it supports horizontal scaling.
Most SQL databases support vertical scaling, which means we can scale the database by adding more RAM, cores, or SSD disk. Butvertical scaling is not the best way to scale the database.
On the other hand, no SQL database likeMongodb supports horizontal scaling, which means you can quickly scale mongodb by adding more servers. This process is also known as Sharding.
Mongodb vs SQL reliability and Availability
Most SQL databases are designed to run as standalone. Later, to build reliability and Availability, their architecture moved towards a distributed database, where the database runs on a cluster of nodes.
On the other hand, Mongodb is designed to keepreliability and Availability in mind. The cluster can easily handle node failure and replication. We don’t need to put a lot of effort into making mongodbreliable and Available.
Mongodb vs SQL schema
Almost all SQL databases follow standard Structured Query Language or SQL. SQL queries are easy to learn and developer-friendly. Users can perform advanced analytics functions like filters, merge, joins, and aggregation on the data, making SQL a powerful option for performing advanced analytics.
On the other hand,mongodb does not support SQL queries.MongoDB supports document querying using JSON format, but this feature is not as rich as SQL and has a few limitations. Mongodb queries do not support joins which is very crucial while performing analytics.
When to use SQL vs No-sql
Use MongoDB in the below scenarios:
- In MongoDB, we don’t have to define the schema before inserting a record, so it can handle data that follow any structure. So in the case where you have to save unstructured data, then mongoDB is the best database to fulfill your requirement.
- If you are handling massive data and in the future, the data will keep growing in such a case, go for mongoDB.
- Go for mongoDB if most of your applications are cloud base.
- Use mongoDB if you need Automatic failover and replication because mongodb was built to keepreliability and availability in mind.
Use SQL database in the below scenarios:
- SQL databases are an ideal choice if your data is structured and follows a specific pattern.
- Always Choose a SQL database if you need to perform joins frequently.
- SQL databases can be a better choice if you have fewer resources and perform small queries.
- SQL excels over mongoDB the ease of use as SQL database supports standard SQL queries which are comparatively easy to learn and implement.
- Go for an SQL database if you need transactional and ACID-compliant out-of-the-box.
This article has started with a brief introduction to MongoDB and SQL databases. We also explored the advantages, disadvantages, and features of MongoDB and SQL databases. Finally, we have seen the difference between MongoDB and SQL and when to choose one over another.
I hope you like this tutorial. Please let me know in the comment box if you face any difficulty.
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