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When to Use MongoDB Rather than MySQL

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MySQL and MongoDB represent two sides of an argument that has been raging recently concerning data storage — the tried and tested relational database vs. non-relational or No-SQL database. They are both open-source products distributed under a version of the GNU GPL, and both are also available as commercial versions offering many more features and corporate support.

We all know that in the database technology world, it comes down to two main database types — SQL (relational) and NoSQL (non-relational). The differences between them are rooted in the way they are designed, which data types they support, and how they store them.

Relational Database Management System (RDBMS)

RDBMS Database is a relational database. It is the standard language for relational database management systems. Data is stored in the form of rows and columns in RDBMS. The relations among tables are also stored in the form of the table SQL (Structured query Language) is a programming language used to perform tasks such as update data on a database, or to retrieve data from a database. Some common relational database management systems that use SQL are: Oracle, Sybase, Microsoft SQL Server, Access, etc.

Features of RDBMS

Limitations for SQL database

Scalability: Users have to scale relational database on powerful servers that are expensive and difficult to handle. To scale relational database, it has to be distributed on to multiple servers. Handling tables across different servers is difficult.

Complexity: In SQL server’s data has to fit into tables anyhow. If your data doesn’t fit into tables, then you need to design your database structure that will be complex and again difficult to handle.

Popular SQL databases and RDBMS’s

• Oracle — an object-relational DBMS written in the C++ language. If you have the budget, this is a full-service option with great customer service and reliability. Oracle has also released an Oracle No-SQL database.

• MS SQL Server — a Microsoft-developed RDBMS for enterprise-level databases that supports both SQL and No-SQL architectures.

NoSQL commonly referred to as “Not Only SQL”. With NoSQL, unstructured, schema less data can be stored in multiple collections and nodes and it does not require fixed table sachems, it supports limited join queries, and we scale it horizontally.

Benefits of NoSQL

highly and easily scalable

Relational database or RDBMS databases are vertically Scalable When load increase on RDBMS database then we scale database by increasing server hardware power, need to by expensive and bigger servers and NoSQL databases are designed to expand horizontally and in Horizontal scaling means that you scale by adding more machines into your pool of resources.

Maintaining NoSQL Servers is Less Expensive

Maintaining high-end RDBMS systems is expensive and need trained manpower for database management but NoSQL databases require less management. it supports many Features like automatic repair, easier data distribution, and simpler data models make administration and tuning requirements lesser in NoSQL.

Lesser Server Cost and Open-Source NoSQL databases are cheap and open source. NoSQL database implementation is easy and typically uses cheap servers to manage the exploding data and transaction while RDBMS databases are expensive and it uses big servers and storage systems. So the storing and processing data cost per gigabyte in the case of NoSQL can be many times lesser than the cost of RDBMS.

No Schema or Fixed Data model

NoSQL database is schema less so Data can be inserted in a NoSQL database without any predefined schema. So the format or data model can be changed any time, without application disruption. And change management is a big headache in SQL.

Support Integrated Caching

NoSQL database support caching in system memory so it increases data output performance and SQL database where this has to be done using separate infrastructure.

Limitations & disadvantage of NoSQL

Popular NoSQL Databases

Now that we’ve established the key structural differences between SQL and NoSQL databases, let’s delve into the key functional differences between the two, looking specifically at MySQL and MongoDB as examples.

What is MySQL?

MySQL is a popular open-source relational database management system (RDBMS) that is developed, distributed and supported by Oracle Corporation. Like other relational systems, MySQL stores data in tables and uses structured query language (SQL) for database access. In MySQL, you pre-define your database schema based on your requirements and set up rules to govern the relationships between fields in your tables. Any changes in schema necessitates a migration procedure that can take the database offline or significantly reduce application performance.

MySQL: The SQL Relational Database

The following are some MySQL benefits and strengths:

What is MongoDB?

MongoDB is an open-source, non-relational database developed by MongoDB, Inc. MongoDB stores data as documents in a binary representation called BSON (Binary JSON). Related information is stored together for fast query access through the MongoDB query language. Fields can vary from document to document; there is no need to declare the structure of documents to the system — documents are self-describing. If a new field needs to be added to a document, then the field can be created without affecting all other documents in the collection, without updating a central system catalog, and without taking the system offline.

MongoDB: The NoSQL Non-Relational Database

The following are some of MongoDB benefits and strengths:

• Dynamic schema: As mentioned, this gives you flexibility to change your data schema without modifying any of your existing data.

• Scalability: MongoDB is horizontally scalable, which helps reduce the workload and scale your business with ease.

• Speed: It’s high-performing for simple queries. • Flexibility: You can add new columns or fields on MongoDB without affecting existing rows or application performance.

Reasons to Use a SQL Database

Not every database fits every business need. That’s why many companies rely on both relational and non-relational databases for different tasks. Although NoSQL databases have gained popularity for their speed and scalability, there are still situations in which a highly structured SQL database might be preferable. Two reasons why you might consider a SQL database are:

To prevent the database from becoming a system-wide bottleneck, especially in high volume environments, NoSQL databases perform in a way that relational databases cannot.

The following features are driving the popularity of NoSQL databases like MongoDB, Couch DB, Cassandra, and HBase:

Conclusion

To answer the main question: “when to use MongoDB instead of MySQL?” you need to take into account your project requirements and further goals. MySQL is well-recognized for its high performance, flexibility, reliable data protection, high availability, and management ease. Proper data indexing can solve the issue with performance, facilitate interaction and ensure robustness. But if your “data is unstructured and complex, or if you can’t pre-define your schema, you’d better opt for MongoDB.” And what is more, if you need to handle a large volume of data and store it as documents — MongoDB will help you to meet the challenges.

R Sai Krishna,

Application Developer

I Can Finally Experience Joy

When to Use MongoDB Rather than MySQL

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