MySQL vs. MongoDB: Comparison in data consistency

MySQL and MongoDB: Comparison in data consistency

Introduction:
Data consistency is an important concept in the database system. During data storage and access, the database must ensure data consistency, that is, at any point in time, no matter how many copies there are in the system, they all contain the same data. As two commonly used database systems, MySQL and MongoDB have different implementation methods in terms of data consistency. This article will compare the characteristics and sample codes of MySQL and MongoDB to explore their similarities and differences in data consistency.

1. MySQL data consistency
MySQL is a relational database management system that uses ACID (atomicity, consistency, isolation, durability) transactions to ensure data consistency. In MySQL, by using the InnoDB storage engine, transaction submission and rollback are supported to ensure data consistency.

The following is a sample code that demonstrates transaction operations and data consistency in MySQL:

BEGIN; -- 开启事务
INSERT INTO users (id, name) VALUES (1, 'Tom'); -- 插入一条数据
UPDATE users SET name = 'Jerry' WHERE id = 1; -- 更新数据
COMMIT; -- 提交事务

In the above example, we first inserted a piece of data and then modified it through an update operation data. By putting these two operations in a single transaction, we can ensure that both operations either succeed or fail at the same time. This mechanism ensures the consistency of data operations.

2. Data consistency of MongoDB
MongoDB is a document database that uses the BSON (Binary JSON) document model. In MongoDB, data consistency is achieved through replica sets and sharded clusters.

1. Replica set
   The replica set in MongoDB consists of a master node and multiple slave nodes. The master node is responsible for processing all write operations, and the slave node is responsible for replicating the data of the master node to ensure data consistency.

The following is a sample code that demonstrates the process of creating a replica set in MongoDB:

rs.initiate() -- 初始化副本集
rs.add("mongodb1:27017") -- 添加从节点
rs.add("mongodb2:27017") -- 添加从节点

In the above example, we used rs.initiate()To initialize a replica set and use rs.add() to add slave nodes. Through replica sets, MongoDB ensures data consistency and high availability.

2. Sharded Cluster
   The sharded cluster in MongoDB achieves data consistency by spreading the data across multiple shards. Each shard is an independent MongoDB instance responsible for storing a portion of data. Sharded clusters manage data read and write operations through routers (mongos).

The following is a sample code that demonstrates the process of creating a sharded cluster in MongoDB:

sh.addShard("mongodb1:27017") -- 添加分片
sh.addShard("mongodb2:27017") -- 添加分片
sh.enableSharding("database") -- 启用分片，指定要分片的数据库
sh.shardCollection("database.collection", { "_id": "hashed" }) -- 分片集合

In the above example, we used sh.addShard() To add sharding, use sh.enableSharding() to enable sharding, and use sh.shardCollection() to specify the collection to be sharded. Through sharded clusters, MongoDB can handle large-scale data and ensure data consistency.

Summary:
MySQL and MongoDB are two different types of database systems with different implementation methods in terms of data consistency. MySQL ensures data consistency through ACID transactions, while MongoDB achieves data consistency through replica sets and sharded clusters. Based on actual needs, we can choose an appropriate database system to meet data consistency requirements.

Reference materials:

1. MySQL Documentation - https://dev.mysql.com/doc/
2. MongoDB Documentation - https://docs.mongodb. com/

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