We use KT's in-memory database in a scientific computing application I work on (to store a graph 30-100GB in size accessed by 100-1000 workers). The performance

We use KT's in-memory database in a scientific computing application I work on (to store a graph 30-100GB in size accessed by 100-1000 workers). The performance is very impressive, and it's been reliable for our use case. But I don't think I'd recommend anyone use it in 2019 -- having an active community (and someone to actively maintain the software!) is too important. A small performance gain over alternatives like Redis is probably not worth the tradeoff of using software that is (sadly) abandoned. edit: That's not to say it is really in need of much development -- it's pretty feature-complete. But it's undergone a bit of software rot: the Debian package, for example, ships header files which fail to compile under many recent gcc versions. And the network effect is just not there. If you run into some database slowness, searching the Web for "Redis performance problem" might get you some ideas. Searching for "kyototycoon performance problem" will get you nowhere.