Question: What are the types of replication in MongoDB?

Answer

MongoDB uses replication to ensure data redundancy and high availability. Replication involves copying data from one database server (the primary) to one or more servers (the secondaries). The primary database handles all write operations, while the secondaries replicate the data and can handle read operations. There are two main types of replication in MongoDB:

1. Replica Sets: This is the default mode of replication in MongoDB. A replica set consists of multiple copies of the same data. One node is designated as the primary node, which receives all write operations. The other nodes, called secondary nodes, replicate the primary's data. Replica sets provide automatic failover and data redundancy. If the primary node fails, one of the secondary nodes is automatically elected to be the new primary.

   Example configuration:

   rs.initiate({
     _id: 'myReplicaSet',
     members: [
       { _id: 0, host: 'mongodb0.example.net:27017' },
       { _id: 1, host: 'mongodb1.example.net:27017' },
       { _id: 2, host: 'mongodb2.example.net:27017' }
     ]
   })

2. Sharded Clusters: While not a replication type per se, sharded clusters use replication internally. Sharding distributes data across multiple machines. A sharded cluster consists of shard nodes, config servers, and query routers (mongos). Each shard in a sharded cluster is a replica set, providing both data distribution and redundancy.

   • Shard Nodes: Store actual data. They are organized into replica sets.
   • Config Servers: Store metadata about the cluster. Typically, there are three config servers in a cluster.
   • Query Routers (mongos): Interface between client applications and the sharded cluster. They route queries to the appropriate shard(s).

In practice, these types of replication work together to provide scalable, highly available data storage solutions. Replica sets ensure that data is redundant and remains available in the event of hardware failure or maintenance operations, while sharding allows for horizontal scaling across multiple servers or even data centers.