MySQL vs. MongoDB: Key Differences Developers Should Know

MySQL and MongoDB: Key differences that developers should know

Introduction:
During the development process, choosing a suitable database management system is crucial. MySQL and MongoDB are two very common database management systems with different features and uses. This article will highlight the key differences between MySQL and MongoDB and give some code examples to help developers better understand them.

1. Data model
MySQL is a relational database that uses tabular form to store data. Each table has a predefined structure with rows and columns. Relational databases are suitable for processing structured data, such as financial data, user information, etc. The following is an example of MySQL creating a table:

CREATE TABLE users (
    id INT AUTO_INCREMENT PRIMARY KEY,
    name VARCHAR(50) NOT NULL,
    age INT
);

MongoDB is a document-oriented database that stores data in BSON (Binary JSON) form. Each document can have a different structure, represented using key-value pairs, and a collection can contain documents of different structures. Document databases are suitable for processing unstructured data, such as logs, social media information, etc. The following is an example of MongoDB inserting documents:

db.users.insertOne({
    name: "John Doe",
    age: 30
});

2. Query language
MySQL uses Structured Query Language (SQL) for data query and operation. Developers can use SQL statements to write queries and modify data. The following is an example of a MySQL query:

SELECT * FROM users WHERE age > 25;

MongoDB uses a JavaScript-style query language for data query and manipulation. Developers can use the query API provided by MongoDB to write queries and modify data. The following is an example of a MongoDB query:

db.users.find({ age: { $gt: 25 } });

3. Flexibility and scalability
MySQL is very powerful in processing structured data and supports complex relationships and connections. However, MySQL scales poorly when data size grows. Under high load conditions, MySQL may experience performance bottlenecks. In addition, MySQL requires predefined table structures and may not be flexible enough for dynamic data storage.

MongoDB is very flexible in handling unstructured data, supporting dynamic structures and nested documents. MongoDB scales easily, supporting horizontal scaling and sharding. This makes MongoDB ideal for handling large amounts of unstructured data. The following is an example of MongoDB inserting nested documents:

db.users.insertOne({
    name: "Jane Smith",
    age: 32,
    address: {
        street: "123 Main St",
        city: "New York",
        country: "USA"
    }
});

4. Transaction support
MySQL is a database that supports transactions, which can ensure the consistency and integrity of data. Transactions can ensure that a set of operations is atomic, that is, either all operations are executed successfully, or all operations fail and are rolled back. The following is an example of a MySQL transaction:

START TRANSACTION;
INSERT INTO orders (user_id, product_id) VALUES (1, 100);
UPDATE inventory SET quantity = quantity - 1 WHERE product_id = 100;
COMMIT;

MongoDB did not support transactions in earlier versions, but since MongoDB version 4.0, transaction support has been introduced. Developers can use transactions to ensure the atomicity of multiple operations. The following is an example of a MongoDB transaction:

session.startTransaction();
db.orders.insertOne({ user_id: 1, product_id: 100 }, { session });
db.inventory.updateOne({ product_id: 100}, { $inc: { quantity: -1 } }, { session });
session.commitTransaction();

Conclusion:
When choosing a database management system, developers need to weigh various factors based on requirements and data characteristics. MySQL is suitable for processing structured data and has powerful relationship and connection functions. MongoDB is suitable for processing unstructured data, has flexibility and good scalability. We hope that the introduction and examples in this article can help developers better understand the key differences between MySQL and MongoDB, and thus better choose a database management system suitable for their projects.

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