Many times I read that data in NOSQL databases is stored denormalized. For instance consider a chess game record. It may not only contain the player id's that participate in the chess game, but also the first and lastname of that player. I suppose this is done because joins are not possible in NOSQL, so if you just duplicate data you can still retrieve all the data you want in one call without manual application level processing of the data.
What I don't understand is that now when you want to update a chess-player's name, you will have to write a query that updates both the chess-game records in which that player participates as well as the player record of that player. This seems like a huge performance overhead as the database will have to search all games where that player participates in and then update each of those records.
Is it true that data is often stored denormalized like in my example?
You are correct, the data is often stored de-normalized in NoSQL databases.
The problem with the updates is partially where the term "eventual consistency" comes from.
In your example, when you update the player's name (not a common event, but it can happen), you would issue a background job to update the name across all other records. Yes, while the update is happening you may retrieve an older value, but eventually the data will be consistent. Since we're not writing ATM software here, the performance/consistency tradeoff is acceptable.
You can find more info here: http://www.allbuttonspressed.com/blog/django/2010/09/JOINs-via-denormalization-for-NoSQL-coders-Part-2-Materialized-views