Difference between Sharding And Replication on MongoDB

Answering Saad's followup answer:

Also you can have shards and replicas together on the same server, it is not recommended way of doing it. Each server should have a single role in the system. If for example you decide to have 2 shards and to replicate it 3 times, you will end up with 6 machines.

I know that this might sound too costly, but you have to remember that this is a commodity hardware and if the service you providing is already so good, that you think about high availability and does not fit one machine, then this is a rather cheap price to pay (in comparison to a dedicated one big machine).

I am writing it as an answer but actually its a question to @Salvador Sir's answer.

Like you said that in sharding 75 GB data "may be" stored as 25GB data on server-1, 25GB on server-2 and 25Gb on server-3. (this distribution depends on the Sharding Key)...then to prevent it from loss we also need to replicate the shard. so this means now every server contains it shards and also the replication of other shards present on other server..means Server-1 will have

1) Its own shard.

2) Replication of Shard present on server-2

3) Replication of Shard present on server-3

same goes with Server-2 and server-3. Am i right?..if this is the case then each server again have 75GB of data again. Right or wrong?

Lets try with this analogy. You are running the library.

As any person who has is running a library you have books in the library. You store all the books you have on the shelf. This is good, but your library became so good that your rival wants to burn it. So you decide to make many additional shelves in other places. There is one the most important shelf and whenever you add some new books you quickly add the same books to other shelves. Now if the rival destroys a shelf - this is not a problem, you just open another one and copy it with the books.

This is replication (just substitute library with application, shelf with a server, book with a document in the collection and your rival is just failed HDD on the server). It just makes additional copies of the data and if something goes wrong it automatically selects another primary.

This concept may help if you

• want to scale reads (but they might lag behind the primary).
• do some offline reads which do not touch main server
• serve some part of the data for a specific region from a server from that specific region
• But the main reason behind replication is data availability. So here you are right: if you have 75Gb of data and replicate it with 2 secondaries - you will get 75*3 Gb of data.

Look at another scenario. There is no rival so you do not want to make copy of your shelves. But right now you have another problem. You became so good that one shelf is not enough. You decide to distribute your books between many shelves. You decide to distribute them between shelves based on the author name (this is not be a good idea and read how to select sharding key here). So everything that starts with name less then K goes to one shelf everything that is K and more goes to another. This is sharding.

This concept may help you:

• distribute a workload
• be able to save data which much more then can fit on a single server
• do map-reduce things
• store more data in ram for faster queries

Here you are partially correct. If you have 75Gb, then in sum on all the servers there will be still 75 Gb, but it does not necessarily be divided equally.

But here is a problem with only sharding. Right now your rival appeared and he just came to one of your shelves and burned it. All the data on that shelf is lost. So you want to replicate every shard as well. Basically the notion that

each shard is a replica set

is not true. But if you are doing sharding you have to create a replication for every shard. Because the more shards you have, the bigger is the probability that at least one will die.