distributed memory caching system to improve Scalabil Ity, esp for Data Base-backed systems

• if you're running just 1-2 servers, you might just want to have a local cache on each

Distributed Hashtable

Can store Data Store data

• typically individual records, still have to query Data Store to get a result-set

  • except maybe for reference tables that rarely change

  • also, if you have relatively rare writes, I could see a process of "publishing" to Mem Cached, including a variety of query-result-sets

• have to make sure all your CRUD Data Store-interface functions are consistent in managing the cache

  • hmm, does any ORM have Mem Cached support built in? Is this even realistic? (Maybe just have a flag to turn it on for some simple tables?)

  • [BeaKer] is a PyThon/WSGI session/cache library which can support Mem Cached as a back end. But it looks like you have to manage that cache by hand...

Can store other things as well, such as whole pages (or chunks of HTML): save the whole HTML-render-cycle.

Each client-library has it's own cache (because they all implement lots of details differently), so if you use multiple languages on your site this is going to be a problem.

Http Caching? No. But if you have a very CRUD/ReST model, the 2 have a lot of similarities....

http://en.wikipedia.org/wiki/Memcached

http://www.danga.com/memcached/

http://smoothspan.wordpress.com/2007/09/23/memcached-when-you-absolutely-positively-have-to-get-it-to-scale-the-next-day/

[Pg Mem Cache] is an interface to Mem Cached for Postgre S Q L

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