Well I can’t speak to MS sql-Server because all of our clients run
Postgresql ;).. I can tell you we have many that are in the 500GB -
1.5TB range.All perform admirably as long as you have the hardware behind it and are
doing correct table structuring (such as table partitioning).Sincerely,
–Joshua D. Drake
We have several TB database in production and it works well on
HP rx1620 dual Itanium2,MSA 20,running Linux. It’s read-only storage for
astronomical catalogs with about 4-billions objects. We have custom
index for spherical coordinates which provide great performance.–Oleg
I had a client that tried to use Ms sql Server to run a 500Gb+ database.
The database simply colapsed. They switched to Teradata and it is
running good. This database has now 1.5Tb+.Currently I have clients using postgresql huge databases and they are
happy. In one client’s database the biggest table has 237Gb+ (only 1
table!) and postgresql run the database without problem using
partitioning,triggers and rules (using postgresql 8.2.5).–Pablo
I think either would work; both Postgresql and MS sql Server have
success stories out there running VLDBs. It really depends on what you
know and what you have. If you have a lot of experience with Postgres
running on Linux,and not much with sql Server on Windows,of course the
former would be a better choice for you. You stand a much better chance
working with tools you know.–Pablo Alcaraz
All of those responses have cooked up quite a few topics into one. Large
databases might mean text warehouses,XML message stores,relational
archives and fact-based business data warehouses.The main thing is that TB-sized databases are performance critical. So
it all depends upon your workload really as to how well Postgresql,or
another other RDBMS vendor can handle them.Anyway,my reason for replying to this thread is that I’m planning
changes for Postgresql 8.4+ that will make allow us to get bigger and
faster databases. If anybody has specific concerns then I’d like to hear
them so I can consider those things in the planning stages.–Simon Riggs
