MongoDB - Database vs Collection memory-wise
MongoDB - Database vs Collection memory-wise


As you said you have MongoDB version 2.4, the MongoDB documentation here and here specifications

WiredTiger Storage Engine


Starting in MongoDB 3.2, the WiredTiger storage engine is the
default storage engine.
Minimum log record size for WiredTiger is 128 bytes. If a log record
is 128 bytes or smaller, WiredTiger does not compress that record.


Memory Use

With WiredTiger, MongoDB utilizes both the WiredTiger internal cache and the filesystem cache.

Starting in 3.4, the WiredTiger internal cache, by default, will use the larger of either:

50% of (RAM - 1 GB), or
256 MB.


By default, WiredTiger uses Snappy block compression for all collections and prefix compression for all indexes. Compression defaults are configurable at a global level and can also be set on a per-collection and per-index basis during collection and index creation.


  Note : For existing deployments, if you do not specify the --storageEngine or the storage.engine setting, the version 3.2+ mongod instance can automatically determine the storage engine used to create
  the data files in the --dbpath or storage.dbPath.


MMAPv1 Storage Engine


MMAPv1 is the default storage engine for MongoDB versions 3.0 and
earlier.
MongoDB 4.0 deprecates the MMAPv1 Storage Engine and will remove
MMAPv1 in a future release. To change your MMAPv1 storage engine
deployment to WiredTiger Storage Engine, see:

a.) Change Standalone to WiredTiger

b.) Change Replica Set to WiredTiger

c.) Change Sharded Cluster to WiredTiger


Memory Use

With MMAPv1, MongoDB automatically uses all free memory on the machine as its cache. System resource monitors show that MongoDB uses a lot of memory, but its usage is dynamic. If another process suddenly needs half the server’s RAM, MongoDB will yield cached memory to the other process.

Technically, the operating system’s virtual memory subsystem manages MongoDB’s memory. This means that MongoDB will use as much free memory as it can, swapping to disk as needed. Deployments with enough memory to fit the application’s working data set in RAM will achieve the best performance.


  For example i need to have 5 collections, each collection is about
  10GB. What is the difference in performance, with emphasis on memory
  usage, between assigning each said collection to a database, versus
  having all of these collections in the same database?


As per google group forum by Mr.Kevin Adistambha defined here it is not advisable to push any technology to such extreme numbers without careful thought due to security, availability, and performance issue.  

MongoDB is perfectly capable of doing 5 collections , as each collection with 10 GB in a single database.

The page MongoDB Limits and Thresholds describes the limits of MongoDB capabilities in detail.

For further your ref here and here