sky-benches VS MapDB

UPDATE: I have published some initial benchmarks against KeyDB here: https://github.com/ohsayan/sky-benches. Oddly enough, the bump in the number of queries in KeyDB is similar to that of Skytable. If anyone has suggestions or find something to be anomalous, please open an issue!

I decided to start with an overview of what open-source options are currently available. When it comes to the implementation of the on-heap cache mechanism, the options are numerous – there is well known: guava, ehcache, caffeine and many other solutions. However, when I began researching cache mechanisms offering the possibility of storing data outside GC control, I found out that there are very few solutions left. Out of the popular ones, only Terracotta is supported. It seems that this is a very niche solution and we do not have many options to choose from. In terms of less-known projects, I came across Chronicle-Map, MapDB and OHC. I chose the last one because it was created as part of the Cassandra project, which I had some experience with and was curious about how this component worked:

So, it's an object database, like Zope's ZODB on Python?

I like the idea, but I'd like to learn about use cases for it.

Otherwise, in Java, MapDB is about as far as I'd be willing to go: https://github.com/jankotek/mapdb/

Anyway, without further ado, I found MapDB (https://github.com/jankotek/mapdb) which does exactly that. Of course, they also provide their own Java collection implementations as well, so I suspect using it with Vavr would be a poor idea, but it is very cool in its own right anyway. Of course, there is also Apache Derby and HSQLDB, and those great options with a long history as well. I haven't played with these in a while though, so I might give them a try again soon for some personal stuff.

In Java I like

https://mapdb.org/

It is more feature rich than you want but in Python I'd probably just use sqlite3 since it is in the standard library.

I have had good results with mapdb