MapDB VS Jedis

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

Finding out what's causing that was not that simple as Jedis does not write a lot of log information when the log level is set to debug. From what we could tell from the Jedis source code it seems that when the Jedis client connects to the configuration endpoint it fetches all known hosts. It stores that in a local cache and figures out the primary node from the set of nodes. Once the primary node is known it will execute operations against the primary node. It does so by connecting to the Amazon-generated domain name/entry and when that entry is down / unreachable it seems it does not use the configuration endpoint to rediscover the nodes or fetch the new cluster topology. We initially thought this had to do with the DNS caching of the JVM, so we also tried to disable caching, but we did not see any effect after that change.

jedis is used to interact with Redis.

Como um bônus, deixo aqui uma classe SessionManager pra ajudar na implementação em Java usando Jedis e o gerador de token do Tomcat, que já é normalmente incluído no Spring Boot: