Comprehensive comparison between MySQL and MongoDB
Generally, the database management system is the foundation of every aspect of life. With the help of technology, we can retrieve the desired information at any time because of the organized nature of data. In this regard, we have two of the most widely used and competitive database services i.e MongoDB and MySQL.
In this article, we’re going to learn the difference between MySQL and MongoDB. We’ll walk you through the features and differences.
Introduction
MySQL is a popular, free-to-use, and open-source relational database management system (RDBMS). As with other relational systems, MySQL stores data using tables and rows, enforces referential integrity, and uses structured query language (SQL) for data access.MongoDB is also free to use and open source; however, its design principles differ from traditional relational systems. Often styled as a non-relational (or NoSQL) system, MongoDB adopts a significantly different approach to storing data, representing information as a series of JSON-like documents (actually stored as binary JSON, or BSON).
As the above paragraphs already enlightened, the main difference when comparing both databases is that MySQL is relational and MongoDB is a document-based database. Throughout this article, we’ll dig down more into Data Schema, Querying language, Performance, Scalability, Security, and Community.
Data Schema
MySQL database schemas and data models need to be defined ahead of time, and data must match this schema to be stored in the database. This rigid approach to storing data offers some degree of safety but trades this for flexibility. If a new type or format of data needs to be stored in the database, schema migration must occur, which can become complex and expensive as the size of the database grows.MongoDB uses dynamic schemas by default, sometimes called schema-less. The documents in a single collection do not need to have the same set of fields, and the data type for a field can differ across documents within a collection. You can change document structures with dynamic schemas at any time. Schema governance is available, however. Starting in MongoDB 3.6, MongoDB supports JSON schema validation, which you can turn on in your validator expression.
Scalability
MongoDB databases can be scaled both vertically and horizontally ( horizontal scaling also known as Scaling out means adding additional nodes or machines to your infrastructure to match new demands whereas vertical scaling is adding more power to your existing machine, for example, upgrading CPU and RAM ).MySQL Database can be scaled vertically ( Scaling vertically means adding more power to your existing machine for example upgrading CPU and RAM).
Performance
MySQL is optimized for high-performance joins across multiple tables that have been appropriately indexed. In MongoDB, joins are supported with the $lookup operation, but they are less needed due to the way MongoDB documents tend to be used; they follow a hierarchical data model and keep most of the data in one document, therefore eliminating the need for joins across multiple documents.MongoDB is also optimized for write performance and features a specific insertMany() API for rapidly inserting data, prioritizing speed over transaction safety wherein MySQL data needs to be inserted row by row.
Observing some of the high-level query behaviors of the two systems, we can see that MySQL is faster at selecting a large number of records, while MongoDB is significantly faster at inserting or updating a large number of records.
Security
MongoDB leverages the popular role-based access control model with a flexible set of permissions. Users are assigned to a role, and that role grants them specific permissions over data sets and database operations. All communication is encrypted with TLS, and it’s possible to write encrypted documents to MongoDB data collections using a master key which is never available to MongoDB, achieving encryption of data at rest.MySQL supports the same encryption features as MongoDB; its authentication model is also similar. Users can be granted roles but also privileges, giving them permissions over particular database operations and against particular data sets.
| MongoDB | MySQL |
|--------------------------------------------|----------------------------------- |
| Efficient in bulk insertion | Efficient in selecting bulk data |
| Use TLS(Transport layer security) | Use TLS(Transport layer security) |
| Efficient in replication(sharding) | Not efficient in replication |
| Best for Unstructured/Semi-structured Data | Best for Structured Data |
| Horizontal scaling(both read / write) | Vertical scaling Horizontal scaling|
| | (multiple read and single write |
| | replica |
| No schema enforcement | Schema enforcement |
| Referential integrity | Referential integrity |
| Transactions (ACID) | Transactions |
| Flexible (Easy to build and enchance | Not Flexible(Complex schema |
| application over time) | migration processes) |
| No down time during Scaling | Down time during scaling |
| MongoDB Query Language(MQL) | Structured Query Language(SQL) |
| JSON support | Doesn’t support JSON |
Conclusion
By now, we have a good understanding of MongoDB and MySQL. In simpler words, MongoDB is a document-Oriented NoSQL database that is used for handling Unstructured data whereas MySQL is an Open source RDBMS that uses SQL to operate and retrieve data in a database and follows a specific row-table-based schema.
Now, the question is what to choose between MongoDB and MySQL. The answer to it is simple: it all depends on various factors such as which type of data you are working on (whether it is structured or unstructured), your needs, and system requirement.