Hi, since the last mails I am are working on an idea of a federated DB - so we would use two separate DBs on two machines. The application is designed to synchronize the stored data over Atom Feeds (not because of the last problem, but as a main feature of the app). Since it is not critical to be always 100% synchronized this concept is an option. We will gain some benefits in parallel reading-time and availability. Additionally, we can use the our Backend without changes.
Sincerely, Lukas -----Original Message----- From: Alex Mizrahi [mailto:alex.mizr...@gmail.com] Sent: Samstag, 7. Mai 2011 18:20 To: elephant-devel@common-lisp.net Subject: Re: [elephant-devel] using one store with mutiple lisp instances > I am curious why the postgres backend is so unpopular. I would not recommend postgres backend as a default choice because it has its own "peculiarities". Particularly, it requires a discipline with use of types, as only strings and (64-bit) integers are properly sorted. Another major drawback is that there is no GC for blobs so it requires export/import to reclaim space from time to time. But if using multiple machines is a requirement then it looks like postgres is the only option, as Oracle confirms that use of BDB DB on remote filesystem doesn't work for multiple clients: http://download.oracle.com/docs/cd/E17076_02/html/programmer_reference/env_r emote.html > As far as I > know there is no real data to support that it is slow in "real world" > applications. There is certain overhead when working with blobs, so it is slower than it might be in theory. But whether it is "slow" is another question. DB can bottleneck in multiple places (disk operations, concurrency locks, network...) so there is no simple answer. To get a good performance with postgres backend one needs to understand that each DB-related operation means a DB query (which potentially goes over the network). So it is a good idea to structure code in a way that minimizes number of slot reads/writes, range queries etc. > It also has caching mechanisms that > work in multi-process applications. Yeah, this gives some freedom with slot reads (although still has some overhead comparing to CLOS slot reads). If we implement cache for range queries as well we can get to a situation where almost nothing is read from DB as long as there is enough memory for cache. This would have a huge impact of DB performance, I think. Another possible improvement is to reimplement cache synchronization with notifications instead of DB tables, as this might drastically reduce overhead of cache synchronization. (Update notifications won't be written to disk.) > why should berkeley db have an edge in that case? With improved caching probably postgres will have an edge for common applications. _______________________________________________ elephant-devel site list elephant-devel@common-lisp.net http://common-lisp.net/mailman/listinfo/elephant-devel _______________________________________________ elephant-devel site list elephant-devel@common-lisp.net http://common-lisp.net/mailman/listinfo/elephant-devel
