MongoDB vs. MySQL: Which Database is Best for Your Project?

There are various databases available on the market, and numerous discussions arround which one is better and why. The most standard option, popular among many companies, is MySQL, but it has some issues related to storing and managing information with changing requirements.

New companies want to find an ideal variant. So, what will be the optimal choice for most businesses: use the standard and understandable MySQL or try something new such as MongoDB? Let’s try to compare these variants and determine optimal choice for your project.

Overview of MongoDB and MySQL

Prior we will dive into all the small aspects of comparison, let’s start with a short overview of both databases.

Introduction to MongoDB

MongoDB is a non-relational type of database that is recommended for the storage of a huge volume of information. It was released in 2009 and supports various OSs including Linux, Windows, and macOS.

The major difference of MongoDB compared with other options is in its method of data storage. The data in this format is stored in JSON-like collections and documents. Such documents are structured in the form of nested docs and arrays. Depending on the document, the value pairs can be structured differently.

This database offers higher speed, better flexibility of data structure, and higher reliability.

Key Features of MongoDB

Here are some key features of MongoDB:

• Indexing. Fields can be indexed as secondary or primary. Such an approach is extremely helpful because it improves the search speed. Users can search a specific index rather than reviewing and checking the entire doc.
• Replication. With the replication feature, it is possible to make copies of the data and then deploy on different servers. This is beneficial for security reasons; backups and disaster management become way easier.
• Sharding. This feature functions by dividing large datasets across various data collections. Users can select a shard key and divide information into various ranges across shards. The shard works as an individual database.
• Ad-hoc queries or temporary commands that are needed for the execution of queries. Among other available options, users can try field searches, regular expressions, and range queries. For real-time analytics, it is possible to update ad-hoc queries with MQL.
• Load balancing. To deal with several requests to various servers at the same time, load balancing is used.
• MongoDB can be used as a file system called GridFS. Such a system contains MongoDB drives, and it is possible to access it via mongofiles utility, lighttpd, or Nginx.
• Aggregation is offered in 3 ways. Pipeline aggregation, single-purpose aggregation, and map-reduce function, as well as capped collections, can be used in MongoDB.  

Common Use Cases for MongoDB

MongoDB can be used for a variety of cases, and some of them are:

• Storage of data for apps.
• Content management systems such as WordPress.
• Cloud-based systems.
• Social networking platforms.
• Maintaining locally based information.
• Asset management.
• High-intensity video games.
• Real-time analytics with high speed.
• Modern payment architecture.

Among the companies that use this type of database, we can mention Zendesk, Twitter, HTC, eBay, Shutterfly, and plenty of others.

Introduction to MySQL

MySQL is a relational database that functions by storing information in the standard tabular format. The data is saved in columns and rows, and it is related. MySQL was created in 1995.

SQL is a programming language that can manage data by extracting, modifying, creating, and deleting information.

The database works on most OSs, specifically on macOS, Windows, Solaris, FreeBSD, and lots of others. It is extremely popular among users because of the easy-to-use interface, great performance, stability, and its features.

There are 2 editions: proprietary Enterprise Server and open-source Community server.

Key Features of MySQL

Here are the main features of MySQL:

• Support of passwords. A password encryption system is necessary for a better security level. That means an unauthorized user can not access the database. Also, in the more recent versions, that is an option for the dual password.
• Clustering and replication. It is possible to copy information from one SQL server to another SQL server, the exclusion without excluding the risks of data loss.
• Online schema. For better flexibility and meeting of the storage requirements, there are available several online schemas.
• Performance schema. With this option, it is possible to monitor server events, track resource utilization, and app performance. This helps to identify some issues early and fix them accordingly.
• Transaction support. There is support for distributed, multi-level, ACID-compliant transactions, and limitless row-level blocking.
• Resilience. MySQL-based apps are resilient to failures, and that directly impacts data availability for various types of apps.
• GUI support. For convenience, there are a variety of tools for designing and creation. With the utilization of such tools, it is possible to speed up the process of administration and development.
• Limitations. There might be some challenges with horizontal scaling.

Common Use Cases for MySQL

Here are some common scenarios of MySQL usage:

• Logging apps.
• Blogs and CMS.
• E-commerce apps with lots of products.
• Social media platforms and those apps that need high-end security.
• LAMP stack.

Among the most popular companies that use this technology, we can specify Sony, Airbnb, Drupal, Netflix, and lots of others.

MongoDB vs MySQL: Side-by-Side DBMS Comparison

Let’s start the comparison with the most obvious and important parameters such as architecture and data storage approach.

System Architecture

Architecture is the basis that forms every system and creates the system where all the features are. That’s why the choice of the architecture is a fundamental thing, and users should understand it prior to the choice of the database.

MongoDB Overview

MongoDB functions on the basis of Nexus Architecture, and it unites the functionalities of relational databases. There is a fantastic option for all the users who are searching for flexible schema, exceptional scalability, and global availability.

Moreover, this type of database has official drivers for such environments as Azure, AWS, and Kubernetes.   

MySQL Overview

It is based on the client-server architecture with the storage optimized for multithreading and high performance. MySQL offers several performance optimization techniques that work with configuration.

Data Storage Approach

MongoDB Format

MongoDB format looks like:

{

  "_id": ObjectId("60f7c29d5b3c2b5a5c4f7b1e"),

  "name": "John Doe",

  "email": "john.doe@example.com",

  "age": 30,

}

Such a format is more flexible, because it is possible to add more data, change it, delete it, and modify it without any problems.

MySQL Format

Here is an example of MySQL:

The information in this format is organized in columns and rows. This structure is more difficult for modification. For every column, there should be a row, and there cannot be a spare column/row.

Schema Design Flexibility

All the databases offer some level of flexibility for changes of schema/design depending on the requirement. If there is no flexibility, it will be extremely challenging to make any even tiny modifications.

MongoDB Schema

MongoDB offers access to a more flexible approach where it is possible to change the design based on the needs. Users can store various types of information and change it without any downtime. Several documents can be stored in one collection that doesn’t have any relation.

The only issues might be that this option lacks joins and transactions, so users should regularly optimize the schema.

MySQL Schema

It is necessary to define tables and columns before saving information. In this structure, every field includes a column and a row. Such an approach gives fewer options for flexibility, and it might impact the speed of development/deployment.

If you require fixed schema, this database is an ideal option. You can achieve better information consistency with MySQL.

Query Languages

The factor of query language is also the most crucial in the choice of the database. You should clearly understand which language will be the most suitable for your project, and that should be done before the installation.

MongoDB Query System

This database uses MQL or MongoDB Query Language. With the help of such a system, it is possible to read, create, update information, as well as conduct text search and geospatial queries.

If you want to find information, it is important to specify doc that has matching properties. To get data, you should use specific query operations, and this database also supports Boolean. However, there is no option for joining operations.

MySQL Query System

MySQL functions on the basis of SQL. It can get information from various tablets, because it supports the join function. This means data can be linked from various tables in the query. That’s why this database is called relational.

SQL has:

• DTL or Data Transaction Language.
• DDL or Data Definition Language.
• DCL or Data Control Language.
• DML or Data Manipulation Language.

Performance and Speed Metrics

Speed metrics and performance characteristics are probably the first criteria that users usually want to know about. During the completion of important tasks, every second is important, and that's why users should be prepared for specific speed metrics.

It is hard to compare various storage approaches regarding the usual benchmarks. That’s why, let’s try to determine higher speed characteristics based on common operations.

MongoDB Performance

This database functions on a doc-based approach and can store huge volumes of unstructured information. It works faster than MySQL. Because the data is stored in a single doc, it is possible to read/write much faster. When working with objects, the performance can also be way faster, because of a Jason-like approach.

Moreover, it is possible to improve performance with some vendor alternatives.

MySQL Performance

Usually, MySQL has a slower performance characteristic when working with huge data volumes. That’s because, when you are searching for specific information, you are going through lots of tables, and that impacts the server loads.

Moreover, there is a certain structure in MySQL so unstructured information cannot be stored there.

Security Features

The percentage of cyberattacks grows with every year, and that’s why security is also one of the main factors to pay attention to. So, let’s find out which database is considered to be more secure and why.

MongoDB Security

This database functions on the principle of role-based access control, where permissions are flexible. Each user can access specific data and conduct certain operations based on the given role.

That means unauthorized users won’t have an opportunity to access information and use it. For an additional security level, there is also TLS encryption and SSL security protocol. It is also possible to write an encrypted doc with the master key.

MySQL Security

This database functions on privilege-based access. This approach also offers encryption methods with authentication, authorization, and auditing. Users receive specific privileges with the help of which they can access certain information and operations.

Recently, there has been also added dual password protection to guarantee an even more secure environment.

Both MySQL and MongoDB offer a somewhat similar level of security, but MySQL is considered more secure. This is because of the schema and rigid architecture.

Scalability Options

Once your project starts growing, you must be able to increase your demands smoothly. If you could not get the needed level of scalability, you will surely notice downtime and frequent lags. Nobody will prefer using crashing apps or web platforms, and your clients will definitely search for a better alternative. That’s why it is crucial to plan scalability of your project beforehand.

MongoDB Scalability

MongoDB is considered to be a very scalable option. Users can access horizontal scaling with the sharding process. Sharding is a division method that works across various machines and collections. This enables launching of the projects with huge data sets.

Depending on the project requirements, it is possible to create a couple of server clusters by adding more servers. Moreover, users can store the data in a cluster with better performance characteristics.

The division of the datasets and loading into several servers also minimized the price when compared with the usage of a single server with expensive hardware. The disc maximization can be achieved with dynamic load balancing in MongoDB.

MySQL Scalability

When discussing MySQL, its scalability has some limitations. There are two available options: vertical scaling and the creation of read replicas. A significant difference between MySQL and MongoDB is that MongoDB offers horizontal scaling with better flexibility. MySQL can scale by increasing RAM and CPU specifications on a single server.

The replications can be added to various servers, but they are read-only, and there are limits on the number of possible replicas. That’s why, if you have apps that require read/write regularly, it can be a huge issue.

Despite the fact that multi-main replication can be used in MySQL, there are still some limitations when compared with MongoDB. The write scale can be added, but only to the specific apps. Also, there is no standard sharding implementation.  

Transaction Handling: ACID vs BASE

Transaction model includes the set of rules for the determination of the data organization, storage, and other manipulations.

The most popular options are:

• BASE (Basic Availability, Soft State, and Eventual consistency).
• ACID (Atomic, Consistent, Isolated, Durable).

The major difference between these 2 options is how they deal with limitations. BASE has a higher availability, while ACID has a more consistent system.

MongoDB Model

This database functions on BASE, and here is how it functions:

• Basically Available. The data spreading and replication are done across various nodes, which are presented in the cluster.
• Soft State. Data values can be changed over time, and the model can break off from the concept of a database.
• Eventually Consistent. This model guarantees eventual consistency, but cannot give immediate one.

MySQL Model

As for MySQL model, it is ACID. Such an approach offers consistency for every transaction. That’s why this model is the most suitable for the companies that are working with analytical processing or online transaction processing.

Here is the functioning of the model:

• Atomic. Each transaction is halted altogether or done properly, and the database reverts to the initial state of the transaction.
• Consistent. Standard database structure impacts the consistency.
• Isolated. That means no transaction can interfere with others.
• Durable. Even when transaction fails because of the network outage or other reason, the data won’t be impacted.

ACID offers higher security standards, and that’s why lots of financial organizations prefer this model over others. Such a model will surely suit businesses that require reliability, more consistency, and a more structured nature of the database.

BASE is a great variant for projects that need simpler scaling and more flexibility.

Usability and Developer Experience

Usability is a very important factor, because you don’t want to waste lots of time on training or hiring new team members. So, let’s determine which database is easier to use for which experts.

MongoDB Ease of Use

The storage process in MongoDB is fairly simple, and lots of users with basic programming skills can utilize it. Unstructured format may be easier for some developers, and it surely gives more flexibility.

Because of the diversity of schemas, this database offers access to a more flexible interface. For instance, IT experts who are now working on the app and don’t require a structured schema will surely benefit from MongoDB.

MySQL Ease of Use

The designed structure is also fairly easy for most users with basic programming experience. Lots of people who want to learn the principles of databases usually start from MySQL. That means that even if you don’t have professionals who are familiar with MySQL, there will definitely be those with SQL database experience.

This option is a great choice for projects that require high security and will benefit from the usage of complex data structures.

Full-Text Search Support

MongoDB

The full-text search support has been added to MongoDB, and it can be easily executed with a certain index type. Moreover, there are options of phase search and term search to simplify the process even more. In addition to this, there is access to Boolean search.

MySQL

The full-text search is also accessible in MySQL. It can be executed with a certain index and facilitated with term search, phrase search, and Boolean search. The limitation appears only in the clustered databases where there is no such option.

Data Replication Capabilities

Replication plays a significant role in the database. It helps to make copies of information and store it whenever it is needed. That is necessary for the backups and improvement of performance and scalability.

MongoDB

The type of replication that is supported by MongoDB is called main-second. With such an approach, a greater number of nodes are available. Here, a single main allows both reads and writes, and there are also read-only servers. With this type of replication, the process functions from the main to the secondary.

This replication type can have less redundancy. That’s why there is a possibility to change this type into replica sets. The replica sets can work with various data copies, where every set has a specific role and can be either secondary or primary. Such an approach is considered to be more robust.

MySQL

MySQL has access to 2 types of replication, such as main-secondary and main-main. That means users can easily replicate data in parallel.

Main-main approach functions in the way that both nodes are mains and replicas. That’s why there is a certain circularity between nodes. With such a type of replication, you can have several main nodes, as well as several secondary ones. The major bonus of such an option is that you can divide the main across the network. So, when one fails for some reason, there may be plenty of others.

Also, in MySQL, there is available group and multi-master cluster replication.

Indexing Strategies

The indexing strategies help with finding data fairly quickly, and that is a usual feature in most of the databases. To understand what indexing strategy works better for you, let’s try to understand them better.

MongoDB

If you don’t know the needed index, then the whole doc will be scanned to find the match. The process is very time-consuming, and there is also no specific structure in MongoDB. Such an approach surely needs more effort and time.

MySQL

When the index is not mentioned, the entire table is scanned during the search. Because MySQL has a strict structure, the process of search can deliver faster results when compared with other types of databases.

Language Driver Availability

MongoDB

There are fewer limitations for the IT specialist who is using this type of database. APIs and drives should be native to the applied programming language.

MySQL

Because of the availability of several functionality layers, there are fewer options for interaction with the data. In addition to this, MySQL has more limitations, and to overcome some of them, it is crucial to plan steps beforehand. The challenges can also occur with experts who are using idiomatic APIs.

Community and Ecosystem

The level of your expertise in the database doesn’t usually matter, because every user can find something new and challenging. That’s why community support is extremely important, because you can learn something new, ask, or even help others and contribute to the community.

Moreover, you should clearly understand which database to select depending on the project requirements.

MongoDB

Because MongoDB is open-source and offers access to a diversity of features, there is strong support for the users.

When talking about the deployment process, the database functions perfectly fine with most of OS as well as being available for SaaS, cloud, and web apps.

MySQL

Because MySQL has a longer history of 20+ years, surely it has more users and a more diverse level of support. Just connect to the community and you can find or ask for any aspect and immediately receive some sort of reply.

The deployment process is extremely simple, and you can build/install it manually if that is something you need. In case you don’t need specific customization for your current project, you can use a binary package for the installation process.

The database function on the most popular OSs and is available for SaaS, web, and cloud apps. For the simplification of installation on Linux systems, there are various package managers available.

Adoption Rate and Popularity

Both these databases are extremely popular, so let’s find out who wins in this battle.

MongoDB

MongoDB is considered to be the top-rated database among the non-relational options. According to the recent analysis, it ranks 7th with a market share of 4.5%. Moreover, lots of huge corporations are using this database, and according to the info, over 7k businesses selected MongoDB.

The main explanation of such popularity is in the scalability and flexibility. The ease of usage and finding needed data also impact the users’ choice immensely.

MySQL

Probably the most popular option is MySQL; users all around the globe have chosen it for many years and even combine it with other databases. According to the recent information, MySQL is in second place after Oracle.

There are lots of explanations for its popularity, among which we can stand out scalability, open-source nature, security, diversity of features, availability, and a huge online community. The number of active users is more than 144k, and market share is approximately 46%.

When Should You Use MongoDB or MySQL?

No ideal and unique option will perfectly suit all the projects. That’s why it is highly recommended to evaluate all the pluses and minuses of the database for your requirements.

Ideal Scenarios for MongoDB

MongoDB is an ideal variant for clients who are searching for quicker data recovery, better availability, and a more automated approach. If you are planning to launch a project with growing and frequently changing requirements, then this is a fanatic scalable solution.

This database is also a great solution for businesses that have most services on the cloud. The native architecture offers such features as sharding and more.  

Ideal Scenarios for MySQL

This database is an optimal choice for companies that don’t have an immediate necessity for scaling. Moreover, if you are currently working on a project that doesn’t require scaling, you can switch to MySQL.

For the organizations with minimal budget and high performance, MySQL is also a perfect choice. Also, this approach is great for finance applications and when there is a necessity for a higher security level.  

Pros and Cons of MongoDB and MySQL

Now let’s proceed to the major pluses and minuses of both databases.

Advantages & Disadvantages of MongoDB

Some of the major advantages are:

• Easiness of up and down scaling.
• Very flexible, so that is way simpler to adapt to the changing requirements.
• Availability of data replication so you won’t lose sensitive information.
• Storage of various data types is available.
• Availability of load balancing, data duplication, so the workflow continues even during hardware failure.
• Indexes for the improvement of search performance.
• It is based on the BASE model for better data availability.

Disadvantages:

• Poorly structured documentation.
• Higher memory usage and lack of built-in analytics.
• At the database level, you won’t implement business logic.
• Insecurity and complexity of transactions.

Advantages & Disadvantages of MySQL

Major advantages are such as:

• Simplest variant in terms of installation and usage. Also, because of the availability of various resources, the troubleshooting process can be fairly easy even for users with basic skills.
• Support for various replication options.
• Managing huge data volumes.
• Availability of privilege-based authentication and generally more secure environment.
• Less overhead when talking about the storage engine.
• Access to reporting and global data distribution that might be beneficial for apps of various sizes.  

Disadvantages:

• Crashes can impact the entire system catalog.
• No caching of procedures.
• It is heavily based on SQL.
• No support for Java or Python integrations.

Licensing and Pricing Models

Both these databases are free and open-source, but for more advanced features, there is access to the paid editions.

MongoDB Editions & Cost

For the small apps, you can deploy everything using the free edition. However, generally there are 3 editions available such as:

• Community server. Free access.
• Enterprise Server. Commercial usage.
• Atlas. Manages cloud database that functions on AWS, Azure, and GCP.

Depending on the needs, you can choose the optimal variant based on the storage, cloud type, or security. The pricing plans are the following:

• Serverless: approximately $0.30 for million reads.
• Dedicated: $57 for the month of usage.
• Shared: free  

MySQL Editions & Cost

Except for the free access, there are also paid versions:

• Cluster CGE: $10,000 for annual usage.
• Enterprise edition: $5000 for annual usage.
• Standard edition: $2,000 for annual usage.

MongoDB vs MySQL: Key Differences and Similarities

Now, let’s dive into the major similarities and diversities of both options.

Commonalities

• Free and open-source variants.
• Availability of the full-text search.
• Powerful query language.
• Index optimization.
• Strong community support.
• Access to the data replication.

Distinct Differences

• Type of database: MongoDB is a non-relational system, whereas MySQL is relational.
• Structure: in MongoDB, data is structured in JSON-like docs, whereas in MySQL, in tabular with columns and rows.
• Architecture: MongoDB has Nexus architecture with better availability and flexibility, and MySQL functions on the basis of client-server architecture.
• Query language: MongoDB uses MQL and MySQL uses SQL.  
• Performance: MongoDB is considered to be faster than MySQL. This is mainly because MySQL stores data in tabular format.
• Security: MySQL is considered to be more secure due to the specific data structure.
• Scalability: MongoDB has horizontal scaling, whereas in MySQL, there is vertical scaling.
• Transaction: MongoDB uses BASE model and MySQL – ACID model.  

Is MongoDB a Viable Replacement for MySQL?

This is a rather generic question that should be answered after reviewing each specific project and its requirements. Sure, there are some scenarios when MongoDB can be the best solution and you should better switch to it, because of the useful features, scalability, flexibility, a performance characteristics.

It is advisable to consider MongoDB when you have noticed such issues as:

• Availability of complex data that cannot be shared in MySQL.
• Huge volumes of data are processed more slowly.
• You have problems with scaling.

However, you can select MySQL, in case you prioritize security or if your project is connected with analytics, marketing, or the financial sector.

Final Thoughts

MySQL and MongoDB are various databases that have lots of diversity in terms of architecture, scalability, security, performance, query language, structure, and more. There are both pluses and minuses in these two databases, and the choice fully depends on your individual project requirements.

There is no ideal solution; you should choose a database depending on the task you are working on. We have covered most aspects and shared deep comparison in the article, so check it once more if you need a specific recommendation.