Schema-less is a bit of a misnomer, it’s better to think of it as:
- SQL = Schema enforced by a RDBMS on Write
- NoSQL = Partial Schema enforced by the DBMS on Write, PLUS schema fully enforced by the Application on Read (Externalised schema)
So while a supposed Schema-less NoSQL data-store will in theory allow you to store any data you like (typically key value pairs, in a document) without prior knowledge of the keys, or data types, it will be pointless unless you have some mechanism to retrieve and use the data. So essentially the schema is partially moved from the RDBMS into the application code. I say partially as you’ll have added Indexes to document collections and or partitioned the data for performance, so the NoSQL DBMS will have a partial schema defined locally, and possibly enforced via Unique constraints.
As to adding additional attributes to a document/object in the store. Depending on how much padding is around the document (un-used space), in it’s physical data block, adding a few more key value pairs to the documents may result in the document having to be physically moved to a larger contiguous block of storage, and the associated indexes re-built. If you plan to use the new keys in a frequently utilised query then you’ll be wanting to also add a suitable new index, which will obviously require some physical storage, take a while to initially build and possibly lead you to ask the sysadmin to allocate more memory to the DBMS, to allow the new index(s) to be cached.
A good start is to read this paper here .Couchbase_Whitepaper_Transitioning_Relational_to_NoSQL