Vert.x VS Ehcache

https://vertx.io/

It's actively maintained with full time developers, performant, supports Kotlin out of the box, and has more features?

Hibernate Reactive integrates with Vert.x, but an extension allows to bridge to Project Reactor if wanted

Have you looked at Vert.x?

Explicitly so:

I really like Eclipse Vert.x... As both an Erlang dev and Java dev, it's a great synergy and soon to have support for Virtual Threads similar to BEAM.

There are many lean, popular, non-magical libraries in Java land. (https://quarkus.io/, https://vertx.io/, etc). Spring is a monster 😱. Its like comparing Kubernetes (written in Go) with some lean framework in another lang.

Eclipse Vert.x - Add amazing Async to any Java stack

Vert.X example: https://github.com/eclipse-vertx/vert.x/blob/master/src/main/java/examples/EventBusExamples.java#L106 (couldn't even find docs)

In fact, it builds on top of proven standards such as Eclipse MicroProfile or frameworks such as Vert.x or JAX‑RS.

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:

If the application is a simple two-tier app with only UI and some form of backend, then we can use a caching layer such as EH Cache or Cache tools to maintain the count of rows as and when we insert it. These caches can be backed by persistence so that the data is not lost. Caches are lightweight and pretty fast. Alternatively, one can store the count in the database itself. The key feature of this approach is that the trigger to update the count is the application's responsibility.

"EHCache" is formally "Ehcache".