"Scott Marlowe" <smarlowe@xxxxxxxxxxxxxxxxx> writes: > Sorry, I think I initially read your response as "Postgres doesn't really get > any faster by breaking the tables up" without the "like that" part. Well breaking up the tables like that or partitioning, either way should be about equivalent really. Breaking up the tables and doing it in the application should perform even better but it does make the schema less flexible and harder to do non-partition based queries and so on. I guess I should explain what I originally meant: A lot of people come from a flat-file world and assume that things get slower when you deal with large tables. In fact due to the magic of log(n) accessing records from a large index is faster than first looking up the table and index info in a small index and then doing a second lookup in up in an index for a table half the size. Where the win in partitioning comes in is in being able to disappear some of the data entirely. By making part of the index key implicit in the choice of partition you get away with a key that's half as large. And in some cases you can get away with using a different key entirely which wouldn't otherwise have been feasible to index. In some cases you can even do sequential scans whereas in an unpartitioned table you would have to use an index (or scan the entire table). But the real reason people partition data is really for the management ease. Being able to drop, and load entire partitions in O(1) is makes it feasible to manage data on a scale that would simply be impossible without partitioned tables. -- Gregory Stark EnterpriseDB http://www.enterprisedb.com