And my response:
To help start to answer your questions, Couchbase uses resources very differently to what you may be experienced with in terms of other database systems and especially MongoDB. Most databases rely heavily on the disk and CPU in order to handle traffic and provide performance. Couchbase, however, is a “memory first” architecture and has a tightly managed cache (based on memcached) that no other technology provides out of the box today. Writes go first into RAM and are eventually written to disk and reads are served directly from RAM without touching disk. This allows Couchbase to utilize RAM much more heavily, and put much less emphasis for performance on the disk and CPU resources. In turn, this allows us to use disk and CPU to accomplish “background” tasks like index maintenance, compaction, etc.
The end result of all this is Couchbase’s ability to handle extremely high levels of traffic, both reads and/or writes, without saturating its resources. We routinely benchmark single nodes up to 200k operations/sec, and that then scales linearly with more nodes being added.
I would suggest that you “tweak” your benchmark in a few ways:
- Try to push the load even higher, almost any database technology can handle 1k ops/sec and you won’t really see the difference in performance between them until you get higher
- Try to measure latency as well as throughput since that’s sometimes even more important to the end-user’s experience
- Try to push more data into the system than you have RAM available. Other technologies (MongoDB especially) start to really suffer when they don’t have enough RAM to cache the entire dataset. Couchbase handles this very very well.
Hope that helps Jamie!
Perry