A message from the same thread that possibly better explains my point:
For Redis on disk to work well, you need:
1) Very biased data access.
2) Mostly reads.
3) Dataset consisting of key->value data where values are small.
4) A dataset that is big enough to really pose memory/cost problems on the ever growing RAM you find in a entry level server.
What is left of Redis semantics and advantages here? The intersection of 1+2+3+4 is small and fits exactly in the case where
Redis for metadata, or as a cache, plus another datastore designed to
work on disk is the right pick. So why should not we focus, instead,
into doing what we already do (the in-memory but persistent data
structure server) better? It would be already an huge success to
enhance what we already have (not to say that Redis is so important, just that Redis can do his small part in the big picture providing something simple that works well, instead of trying to do everything and save the world).
Comments
A message from the same thread that possibly better explains my point:
For Redis on disk to work well, you need:
1) Very biased data access.
2) Mostly reads.
3) Dataset consisting of key->value data where values are small.
4) A dataset that is big enough to really pose memory/cost problems on the ever growing RAM you find in a entry level server.
What is left of Redis semantics and advantages here? The intersection of 1+2+3+4 is small and fits exactly in the case where Redis for metadata, or as a cache, plus another datastore designed to work on disk is the right pick. So why should not we focus, instead, into doing what we already do (the in-memory but persistent data structure server) better? It would be already an huge success to enhance what we already have (not to say that Redis is so important, just that Redis can do his small part in the big picture providing something simple that works well, instead of trying to do everything and save the world).