MongoDB Vs MySQL: Choose Best Database For Your Business

The Companies looking for relational databases worldwide, MySQL database has become one of the go-to-inexpensive options. Choosing the database for apps is a significant challenge. Relational DBMSs like PostgreSQL, MS SQL, and MySQL are rocking the market. Whether you are considering database technology for mobile development or large-scale software solution, the choice is less. There is a big fight between choosing the right database: MongoDB vs MySQL.

MySQL is the most popular and commonly used database for projects and web development. The exponential growth has brought growth and variety of data, and time is changing fast. Non-relational databases like MongoDB are gaining popularity because of diversified, multifaceted and voluminous data growth.

This new class of non-relational database has brought tough competition between the two newbies: MongoDB vs MySQL.

This blog will help enterprises understand the two models and situations where one emerges better than another.

We’ll tell you when to use the best database, so let’s start.

What is MySQL?

We all are aware of MySQL; it is an open-sourced relational database management system currently owned by Oracle corporation. However, MySQL AB built it. Well, MySQL is a veteran, as it has been in the IT industry since 1995.

Like other DBMSs, MySQL uses SQL to access the database and keep data stored in tables. The user can predefine the database scheme based on requirements to establish rules governing the relationship among the relevant fields in the tables. MySQL keeps data in rows and columns and uses SQL to access the data from the tables. It uses a database schema to outline its internal structure. Also, it can push the database to offline mode.

 

Some big names that use MySQL

• Twitter
• Pinterest
• US Navy
• Walmart
• NASA
• YouTube
• Netflix
• Spotify
• Paypal

What is MongoDB?

MongoDB is a non-relational database developed by MongoDB Inc. The idea came in 2007, but the version first released in 2010. Databases in this type of DBMS are stored in a form known as BSON.

The MongoDB query language stores related data for query access. The fields are different for each document, so you will not require to declare the document structure to the systems.

Without making alterations to the other document present in the collection, you can create and add a new field to the document. As the central system catalogue does not require any MongoDB update, you don’t need to take the system to offline mode. By optionally using schema validation, you can also enforce the data control on all collections.

Document model of MongoDB maps objects in the application mode naturally. Because of this, developers find MongoDB easy to master and utilise. With no hassle, users can store arrays by representing hierarchical associations.

NoSQL solutions come with auto-sharding and on-board replication that enhances availability and scalability.

Many successful organisations using MongoDB are:

• T-Mobile
• Klout
• SurveyMonkey
• Citrix
• Sony
• Foursquare
• Twitter
• Zendesk
• MuleSoft
• InVision
• Hootsuite

MongoDB vs MySQL – which is better?

• Database structure

MySQL stores data values in tables and makes use of SQL to access them. For defining database structure, it uses schema. Schema requires rows inside the table and have the same structure with values represented by specific data types.

MongoDB data get stored in JSON-like documents, which come in varied structures. It stores related data sets together and later accesses them with MongoDB query language to better the query speed. As the data is schema-free, it allows mobile app developers to create documents with defining document structures.

• Index optimisation

Both the MongoDB and MySQL databases use indexes for searching data. The difference comes in the approach when the index is not found or defined.

In MySQL, when the index is not defined in index optimisation, the database engine scans the entire table to find relevant rows.

When the index is not found in MongoDB, every single document in the collection is scanned to match the query statement.

• Database deployment

Languages used to write databases for MongoDB are C, C++, and JavaScript. It has binaries for Solaris, Windows, Linux, and OS X.

In the case of MySQL, the languages used to write databases are C and C++, and it contains binaries for Windows, AIX, FreeBSD, HP-US, NetBSD, OS X, Linux, BSDi, IRIX, etc.

 

• Speed and performance

MongoDB controls a large volume of unrestricted data as compared to MySQL. It is because it stores entity data on a single document. It also allows the user to query sensitively towards workload. It makes it easy for users to read and write data in one place.

MySQL is comparatively slow and uses a large volume of data. It struggles to deal with high volumes of unstructured data. It happens because data is scattered over multiple tables, and for reading & writing, it needs to be accessed.

 

• Security model

Auditing, authentication and authorisation are major security features in MongoDB. The users use transport layer security (TLS) and secure sockets layer (SSL) for encryption. It also ensures that only intended clients read the document. MongoDB establishes control over variable sets of privileges.

The security model in MySQL is based on privilege. It means users authenticated by MySQL can get benefits like INSERT, UPDATE, SELECT AND CREATE.

 

• Replication

Using MySQL, the master-slave replication rule dominates. On the other hand, MongoDB offers inbuilt replication, sharding and auto election features. These features make MongoDB versatile and flexible.

MongoDB offers another edge over MySQL by using replica sets, as it can create several copies simultaneously from the same data. Every piece of data in original and replica play the role of primary or secondary source of data. On the primary data set, only read and write operations are done.

• Developer productivity

When we talk about the performance of two, the points fall in the lap of MongoDB.

As MySQL uses a very rigid table structure model, creating applications is much slower.

MongoDB speed up the development cycle by around 4 to 5 times by working with flexible data with JSON documents. For an object-oriented programming language, it maps documents naturally and makes it easy for developers to visualise how application data is mapped in the database.

• The offerings

At three primary levels, MySQL offers an Oracle Lifetime Support;

• Premier for versions 1 – 5 years old
• Extended for versions 6 – 8 years old
• Sustain for versions 9+ years old.

Every level offers 24*7 tech support with complete access to a knowledge base, bug fixes, maintenance releases, updates and patches.

MongoDB provides enterprise-grade support and extends beyond the break/fix model. Provide support to extended life-cycle support add-on round-the-clock; this adds flexibility and upgrades the newer version at its own pace.

When to use MongoDB

• When high data availability is your priority, along with automatic, fast and instant data recovery.

• If you are working on unstable schema and lower the cost of schema migration

• If your services are cloud-based, MongoDB comes in handy for your business because of its native scale-out architecture.

 

When to use MySQL

• When you are just starting your business and in which database won’t scale that much.

• Your data structure which is not going to change over the period

• Fixed schema

• If at a low budget, you are looking for top-notch performance

• If you need a high transaction rate

• If data security is your top priority

 

Which database suits your business needs?

Can MongoDB replace MySQL?

MySQL comes with unique sets of advantages compared to MongoDB. It is difficult to comment with certainty that MongoDB will replace MySQL.

What should you use? MongoDB or MySQL

For quick application building, firms of various sizes and scales prefer MongoDB. It proves handy in dealing with various types of data. Even companies can achieve higher efficiency of application management.

MongoDB automatically eliminates complicated ORM layers. This assists in the translation of objects on the relational tables. You benefit from adjusting schema according to your business needs through a flexible model provided by MongoDB. In the case of MySQL, the user has to carry custom engineering to achieve scaling. All the above reasons compel companies to migrate from MySQL to MongoDB.

We hope this blog helps you make the right choice. If you still have any questions, you can consult our MongoDB database specialist and MySQL developers to guide you as per your project needs.