to tell if MongoDB is good for holding such data, which eventually
will be queried against time ranges (e.g. retrieve all images of a
particular camera between a specified hour)? Any suggestions about
Document Based schema design for my case?
MongoDB can do this. For better performance, you can set an index on your time field.
What should be the specs of server (CPU, RAM, Disk)? any suggestion?
I think RAM and Disk would be important.
- If you don't want to do
sharding to scale out, you should consider a larger size of disk so you can store all your data in it.
- Your hot data should can fit into your RAM. If not, then you should consider a larger RAM because the performance of MongoDB mainly depends on RAM.
Should i consider Sharding/Replication for this scenario (while
considering the performance in writing to synch replica sets)?
I don't know many cameras do you have, even 1000 inserts/second with total 1000 cameras should still be easy to MongoDB. If you are concerning insert performance, I don't think you need to do sharding(Except the data size are too big that you have to separate them into several machines).
Another problem is the read frequency of your application. It it is very high, then you can consider sharding or replication here.
And you can use (timestamp + camera_id) as your sharding key if your query only on one camera in a time range.
Are there any benefits of using multiple databases on same machine, so
that one database will hold images of current day for all cameras, and
the second one will be used to archive previous day images?
You can separate the table into two collections(archive and current). And set index only on archive if you only query date on archive. Without the overhead of index creation, the current collection should benefit with insert.
And you can write a daily program to dump the current data into archive.
