At my work, we have a very big system that runs on many PCs at the same time, with very big tables with hundreds of thousands of rows, and sometimes many millions of rows.
When you make a SELECT on a very big table, let's say you want to know every transaction a user has made in the past 10 years, and the primary key of the table is not built in an efficient way, the query might take several minutes to run.
Then, our application might me running on many user's PCs at the same time, accessing the same database. So if someone tries to insert into the table that the other SELECT is reading (in pages that SQL is trying to read), then a LOCK can occur and the two transactions block each other.
We had to add a "NO LOCK" to our SELECT statement, because it was a huge SELECT on a table that is used a lot by a lot of users at the same time and we had LOCKS all the time.
I don't know if my example is clear enough? This is a real life example.
A SELECT in SQL Server will place a shared lock on a table row - and a second SELECT would also require a shared lock, and those are compatible with one another.
So no - one SELECT cannot block another SELECT.
What the WITH (NOLOCK) query hint is used for is to be able to read data that's in the process of being inserted (by another connection) and that hasn't been committed yet.
Without that query hint, a SELECT might be blocked reading a table by an ongoing INSERT (or UPDATE) statement that places an exclusive lock on rows (or possibly a whole table), until that operation's transaction has been committed (or rolled back).
Problem of the WITH (NOLOCK) hint is: you might be reading data rows that aren't going to be inserted at all, in the end (if the INSERT transaction is rolled back) - so your e.g. report might show data that's never really been committed to the database.
There's another query hint that might be useful - WITH (READPAST). This instructs the SELECT command to just skip any rows that it attempts to read and that are locked exclusively. The SELECT will not block, and it will not read any "dirty" un-committed data - but it might skip some rows, e.g. not show all your rows in the table.
On performance you keep focusing on select.
Shared does not block reads.
Shared lock blocks update.
If you have hundreds of shared locks it is going to take an update a while to get an exclusive lock as it must wait for shared locks to clear.
By default a select (read) takes a shared lock.
Shared (S) locks allow concurrent transactions to read (SELECT) a resource.
A shared lock as no effect on other selects (1 or a 1000).
The difference is how the nolock versus shared lock effects update or insert operation.
No other transactions can modify the data while shared (S) locks exist on the resource.
A shared lock blocks an update!
But nolock does not block an update.
This can have huge impacts on performance of updates. It also impact inserts.
Dirty read (nolock) just sounds dirty. You are never going to get partial data. If an update is changing John to Sally you are never going to get Jolly.
I use shared locks a lot for concurrency. Data is stale as soon as it is read. A read of John that changes to Sally the next millisecond is stale data. A read of Sally that gets rolled back John the next millisecond is stale data. That is on the millisecond level. I have a dataloader that take 20 hours to run if users are taking shared locks and 4 hours to run is users are taking no lock. Shared locks in this case cause data to be 16 hours stale.
Don't use nolocks wrong. But they do have a place. If you are going to cut a check when a byte is set to 1 and then set it to 2 when the check is cut - not a time for a nolock.
The SELECT WITH (NOLOCK) allows reads of uncommitted data, which is equivalent to having the READ UNCOMMITTED isolation level set on your database. The NOLOCK keyword allows finer grained control than setting the isolation level on the entire database.
I have to add one important comment. Everyone is mentioning that NOLOCKreads only dirty data. This is not precise. It is also possible that you'll get the same row twice or the whole row is skipped during your read. The reason is that you could ask for some data at the same time when SQL Server is re-balancing b-tree.
With the NOLOCK hint (or setting the isolation level of the session to READ UNCOMMITTED) you tell SQL Server that you don't expect consistency, so there are no guarantees. Bear in mind though that "inconsistent data" does not only mean that you might see uncommitted changes that were later rolled back, or data changes in an intermediate state of the transaction. It also means that in a simple query that scans all table/index data SQL Server may lose the scan position, or you might end up getting the same row twice.