Dear community, My company, which I actually represent, is a fervent user of PostgreSQL. We used to make all our applications using PostgreSQL for more than 5 years. We usually do classical client/server applications under Linux, and Web interface (php, perl, C/C++). We used to manage also public web services with 10/15 millions records and up to 8 millions pages view by month.
Now we are in front of a new need, but we do not find any good solution with PostgreSQL. We need to make a sort of directory of millions of data growing about 4/8 millions per month, and to be able to be used by many users from the web. In order to do this, our solution need to be able to run perfectly with many insert and many select access (done before each insert, and done by web site visitors). We will also need to make a search engine for the millions of data (140/150 millions records at the immediate beginning) ... No it's not google, but the kind of volume of data stored in the main table is similar. Then ... we have made some tests, with the actual servers we have here, like a Bi-Pro Xeon 2.8 Ghz, with 4 Gb of RAM and the result of the cumulative inserts, and select access is slowing down the service really quickly ... (Load average is going up to 10 really quickly on the database). We were at this moment thinking about a Cluster solution ... We saw on the Internet many solution talking about Cluster solution using MySQL ... but nothing about PostgreSQL ... the idea is to use several servers to make a sort of big virtual server using the disk space of each server as one, and having the ability to use the CPU and RAM of each servers in order to maintain good service performance ...one can imagin it is like a GFS but dedicated to postgreSQL... Is there any solution with PostgreSQL matching these needs ... ? Do we have to backport our development to MySQL for this kind of problem ? Is there any other solution than a Cluster for our problem ? Looking for your reply, Regards, -- Hervé ---------------------------(end of broadcast)--------------------------- TIP 8: explain analyze is your friend