| Subject | Data Partitioning with Firebird |
|---|---|
| Author | Nigel Weeks |
| Post date | 2014-08-06T08:21:31Z |
Hi all,
I've been using Firebird for years, but mainly keeping a very low profile.
I'm planning a Health Informatics project with the University of Tasmania, and as I've used Firebird to power all the other projects, I'm planning on using it again.
The question I have is about data partitioning across servers. Essentially, we're wanting 10 servers to handle the backend - not because it can't do it with one, but we need to show that the DB can scale (investors love clusters).
Initially, as every table is based on bigint primary keys, I could have server 0 handling every record ending in a zero(0,10,20,etc), with duplicated table structures on top.
The middle layer handles the MapReduce, determining which server to ask for data, and combining data sets(reducing) for the app on top. (No, it's not BigData, just an entity mapping layer).
When it comes to data partitioning across servers, what other strategies have people done?
Cheers,
NW.
I've been using Firebird for years, but mainly keeping a very low profile.
I'm planning a Health Informatics project with the University of Tasmania, and as I've used Firebird to power all the other projects, I'm planning on using it again.
The question I have is about data partitioning across servers. Essentially, we're wanting 10 servers to handle the backend - not because it can't do it with one, but we need to show that the DB can scale (investors love clusters).
Initially, as every table is based on bigint primary keys, I could have server 0 handling every record ending in a zero(0,10,20,etc), with duplicated table structures on top.
The middle layer handles the MapReduce, determining which server to ask for data, and combining data sets(reducing) for the app on top. (No, it's not BigData, just an entity mapping layer).
When it comes to data partitioning across servers, what other strategies have people done?
Cheers,
NW.