In Mongo what is the difference between sharding and replication?

Whenever you're thinking about sharding or replication, you need to think in the context of writers/update operations. If you don't need to scale writes then replications, as it fairly simpler, is a good choice for you.

On the other hand, if you workload mostly updates/writes then at some point you'll hit a write bottleneck. If write request comes Mongo blocks other writes request. Those write request blocks until the first request will be done. If you want to scale this writes and want parallelize it then you need to implement sharding.

Just to put this somewhere...

The most basic way to run mongo is as standalone server.

• You write a config (file or cli options)
• initiate the server using mongod

For this picture, I didn't include the "client". Check the next one.

• A replica set is a set of servers initialized exactly as above with a different config file.
• To link them, we connect to one of them, and initialize the replica set mode.
• They will mirror each other (in the most common configuration). This system guarantees high availability of data.

The initialization of the replica set is represented in the red border box.

• Sharding is not about replicating data, but about fragmenting data.
• Each fragment of data is called chunk and goes to a different shard. shard = each replica set.
• "main" server, running mongos instead of mongod. This is a router for queries from the client.

Obvious: The trade-off is a more complex architecture. Novelty: configuration server (again, a different config file).

There is much more to add, but apart from the words the pictures hold much the same.

Even mongoDB recommends to study your case carefully before going sharding. Vertical scaling (vs) is probably a good idea at least once before horizontal scaling (hs).

vs is done upgrading hardware (cpu, ram, etc). hs is needs more computers (but could be cheap computers).

Both replication and sharding can be used (individually or together) for horizontal scaling of a MongoDB installation.

Sharding is MongoDB's solution for meeting the demands of data growth. Sharding stores data records across multiple servers to provide faster throughput on read and write queries, particularly for very large data sets. Any of the servers in the sharded cluster can respond to a read or write operation, which greatly speeds up query responses.

Replication is MongoDB's solution for providing stability, backup, and disaster recovery to a MongoDB installation. This process copies and synchronizes the replica data set across multiple servers. This prevents downtime if one server goes offline.

Any of the secondary servers can respond to read queries, but only the primary server will perform write operations. The results of the write operation will then be propagated out to the secondary servers.

Scenario 1: Fault-Tolerance In this scenario, the user is storing billing data in a MongoDB installation. This data is mission-critical to the user's business, and needs to be available 24/7, even if a server crashes or is taken offline.

MongoDB replication is the best solution for this user. With replication, the entire data set is mirrored on multiple servers. If a server fails or is taken offline, the other servers in the cluster take over.

Scenario 2: High Performance In this scenario, the user is running a social networking site which is run from a MongoDB database. As the social network grows, the MongoDB data set has grown along with it. The user is seeing query times and page loads increase beyond an acceptable point. It is critical that the user's MongoDB installation receives a major performance boost.

Setting up a sharded MongoDB cluster is the best solution for this user. The sharded cluster will break up the user's data set and store parts of it on separate secondary servers. Each secondary server can respond to read or write queries on its portion of the data, which greatly increases the installation's response time

MongoDB Atlas is a Database as a service in could. It support three major cloud providers such as Azure , AWS and GCP. In cloud environment , we usually talk about high availability and scalability. In Atlas “clusters”, can be either a replica set or a sharded cluster. These two address high availability and scalability features of our cloud environment.

In general Cluster is a group of servers used to achieve a specific task. So sharded clusters are used to store data in across multiple machines to meet the demand of data growth. As the size of the data increases, a single machine may not be sufficient to store the data nor provide an acceptable read and write throughput. Sharded clusters supports the horizontal scalability of the underling cloud environment.

A replica set in MongoDB is a group of mongod processes that maintain the same data set. Replica sets provide redundancy and high availability, and are the basis for all production deployments.In a replica, one node is a primary node that receives all write operations. All other instances, such as secondaries, apply operations from the primary so that they have the same data set. Replica set mainly focus on the availability of data.

Please check the documentation

Thank You.