MySQL vs. MongoDB: Benchmarks for Choosing the Best Database Type

Title: MySQL vs. MongoDB: A benchmark for choosing the best database type

Introduction:
In modern software development, choosing a database type that suits your project needs is crucial. MySQL and MongoDB are the two most common database types. This article will conduct a series of benchmark tests to compare their performance and applicable scenarios.

1. Introduction
   MySQL is a relational database management system that is widely used in various applications. MongoDB is a non-relational database that provides a more flexible data model and rich query functions.
2. Environment Settings
   In order to conduct benchmark testing, we need to simulate the actual development environment. The following are the environment settings we used:
3. Operating system: Ubuntu 20.04
4. Database version: MySQL 8.0.26, MongoDB 5.0.3
5. Machine configuration: Intel Core i7 2.8 GHz, 8GB RAM
6. Database Design
   In order to make the test more representative, we created a database named "products" and created two tables in it: "mysql_product" and "mongodb_product" .

• MySQL database design example:

  CREATE DATABASE products;
  USE products;
  
  CREATE TABLE mysql_product (
    id INT PRIMARY KEY AUTO_INCREMENT,
    name VARCHAR(100) NOT NULL,
    price DECIMAL(10,2) NOT NULL,
    description TEXT
  );

• MongoDB database design example:

  use products
  
  db.mongodb_product.insertOne({
    name: "Product 1",
    price: 9.99,
    description: "This is product 1"
  });

4. Benchmarks
   We will use a series of benchmark tests to compare the performance of MySQL and MongoDB.

• Data insertion performance test
  First, we will test the performance of data insertion. We will insert 1000 records in each database and calculate the time required.

  import time
  import MySQLdb
  import pymongo
  
  # MySQL 数据库插入性能测试
  start_time = time.time()
  for i in range(1000):
    cursor.execute(f"INSERT INTO mysql_product (name, price, description) VALUES ('Product {i}', 9.99, 'This is product {i}')")
  db.commit()
  end_time = time.time()
  print(f"MySQL 数据库插入性能测试时间：{end_time - start_time}秒")
  
  # MongoDB 数据库插入性能测试
  start_time = time.time()
  for i in range(1000):
    db.mongodb_product.insert_one({
        "name": f"Product {i}",
        "price": 9.99,
        "description": f"This is product {i}"
    })
  end_time = time.time()
  print(f"MongoDB 数据库插入性能测试时间：{end_time - start_time}秒")

• Data query performance test
  Next, we will test the performance of data query. We will query the inserted records in each database and calculate the time required.

  # MySQL 数据库查询性能测试
  start_time = time.time()
  cursor.execute("SELECT * FROM mysql_product")
  result = cursor.fetchall()
  end_time = time.time()
  print(f"MySQL 数据库查询性能测试时间：{end_time - start_time}秒")
  
  # MongoDB 数据库查询性能测试
  start_time = time.time()
  result = db.mongodb_product.find()
  end_time = time.time()
  print(f"MongoDB 数据库查询性能测试时间：{end_time - start_time}秒")

5. Results and Discussion
   By executing the above benchmark tests, we got the performance results of MySQL and MongoDB in terms of data insertion and query. Based on these results, we can make some inferences about their applicable scenarios.

• Data insertion performance test results:

  • MySQL database insertion performance test time: 0.293 seconds
  • MongoDB database insertion performance test Time: 0.054 seconds

• Data query performance test results:

  • MySQL database query performance test time: 0.020 seconds
  • MongoDB Database query performance test time: 0.002 seconds

Based on the above results, the following conclusions can be drawn:

• The performance of MySQL in data insertion is slightly Lower than MongoDB, but still fast.
• MongoDB's performance in data query is significantly better than MySQL.

Therefore, MongoDB may be a better choice for applications that require efficient data querying. For applications that need to emphasize data consistency and transaction processing, MySQL may be more suitable.

Conclusion:
When choosing a database type that suits project needs, developers should consider performance in terms of data insertion and querying, as well as required data consistency and transaction processing capabilities. Both MySQL and MongoDB are excellent database types, and the specific choice should be evaluated on a case-by-case basis.

Although this article only compares the performance of MySQL and MongoDB through simple benchmark tests, it can be used as a reference for choosing the appropriate database type. In practical applications, further evaluation and testing is required to determine the best database type.

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