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MySQL vs. MongoDB: Comparison on Data Backup and Recovery

王林
Release: 2023-07-13 13:49:22
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MySQL and MongoDB: Comparison in data backup and recovery

Introduction:
Data backup and recovery are a vital part of database management. For the two commonly used database systems, MySQL and MongoDB, how to back up and restore data, as well as the differences, advantages and disadvantages between them, are all things we need to understand and master. This article will compare MySQL and MongoDB in terms of data backup and recovery, and provide code examples to help readers better understand and apply them.

1. MySQL data backup and recovery
MySQL is a relational database management system, and backup and recovery operations are very important.

  1. Data backup:
    MySQL provides a variety of backup methods, including physical backup and logical backup.
  • Physical backup: Back up data files and log files, usually using the tool mysqldump provided by MySQL. The sample code is as follows:
mysqldump -u用户名 -p密码 数据库名 > 备份文件名.sql
Copy after login
  • Logical backup: Back up the logical structure and data content of the data, usually using mysqlhotcopy or xtrabackup. The sample code is as follows:
mysqlhotcopy --user=用户名 --password=密码 数据库名 备份目录
或
innobackupex --user=用户名 --password=密码 备份目录
Copy after login
  1. Data recovery:
  2. Physical recovery: To restore the backup file to the MySQL database, you can use the command line tool mysql or source provided by MySQL. The sample code is as follows:
mysql -u用户名 -p密码 数据库名 < 备份文件名.sql
或
source 备份文件名.sql
Copy after login
Copy after login
  • Logical recovery: To perform backup of the logical structure and data content, you can use the command line tool mysql or source provided by MySQL. The sample code is as follows:
mysql -u用户名 -p密码 数据库名 < 备份文件名.sql
或
source 备份文件名.sql
Copy after login
Copy after login

2. MongoDB data backup and recovery
MongoDB is a NoSQL database for document storage, and the backup and recovery operations are relatively simple.

  1. Data backup:
    MongoDB provides the mongodump tool to back up data. The sample code is as follows:
mongodump --host 主机名 --port 端口号 --db 数据库名 --username 用户名 --password 密码 --out 备份目录
Copy after login
  1. Data recovery:
    MongoDB provides the mongorestore tool to restore data. The sample code is as follows:
mongorestore --host 主机名 --port 端口号 --db 数据库名 --username 用户名 --password 密码 备份目录
Copy after login

3. Comparison of data backup and recovery between MySQL and MongoDB

  1. Backup speed:
    Relatively speaking, MongoDB’s backup speed is faster , because it is a document-based database, the entire database can be backed up directly, and no complex logic is required.
  2. Data recovery:
    MySQL data recovery requires restoring the database structure first and then importing the data, while MongoDB can directly import the backup file.
  3. Size of data backup:
    MongoDB backup files are usually smaller than MySQL backup files because MongoDB uses BSON format, while MySQL uses text format.
  4. Database performance impact:
    MySQL may have a certain impact on the performance of the database during the backup process, especially for large databases. The backup process of MongoDB has relatively little impact on database performance.

Summary:
MySQL and MongoDB have some differences, advantages and disadvantages in data backup and recovery. MySQL's backup and recovery are relatively complicated, requiring you to restore the database structure and then import the data; while MongoDB's backup and recovery operations are relatively simple, and you can directly import the backup file. In addition, MongoDB's backup speed is faster, the backup files are smaller, and the impact on database performance is relatively small.

Conclusion:
Whether it is MySQL or MongoDB, data backup and recovery are an indispensable part of database management. This article compares the data backup and recovery of MySQL and MongoDB, and provides relevant code examples, hoping to help readers better understand and apply the backup and recovery operations of these two database systems.

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