Apache Camel VS mats3

"correct" is a value judgement that depends on lots of different things. Only you can decide which tool is correct. Here are some ideas:

- https://camel.apache.org/

- https://www.windmill.dev/

- https://github.com/huginn/huginn

Your idea about a queue (in redis, or postgres, or sqlite, etc) is also totally valid. These off-the-shelf tools I listed probably wouldn't give you a huge advantage IMO.

Apache Camel Apache Nifi Spring Cloud

This reminds me more of Apache Camel[0] than other things it's being compared to.

> The process initiator puts a message on a queue, and another processor picks that up (probably on a different service, on a different host, and in different code base) - does some processing, and puts its (intermediate) result on another queue

This is almost exactly the definition of message routing (ie: Camel).

I'm a bit doubtful about the pitch because the solution is presented as enabling you to maintain synchronous style programming while achieving benefits of async processing. This just isn't true, these are fundamental tradeoffs. If you need a synchronous answer back then no amount of queuing, routing, prioritisation, etc etc will save you when the fundamental resource providing that is unavailable, and the ultimate outcome that your synchronous client now hangs indefinitely waiting for a reply message instead of erroring hard and fast is not desirable at all. If you go into this ad hoc, and build in a leaky abstraction that asynchronous things are are actually synchronous and vice versa, before you know it you are going to have unstable behaviour or even worse, deadlocks all over your system and the worst part - the true state of the system is now hidden in which messages are pending in transient message queues everywhere.

What really matters here is to fundamentally design things from the start with patterns that allow you to be very explicit about what needs to be synchronous vs async (building on principles of idempotency, immutability, coherence, to maximise the cases where async is the answer).

The notion of Apache Camel is to make all these decisions a first class elements of your framework and then to extract out the routing layer as a dedicated construct. The fact it generalises beyond message queues (treating literally anything that can provide a piece of data as a message provider) is a bonus.

[0] https://camel.apache.org/

Since you're writing a Java app to consume this, I highly recommend Apache Camel to do the consuming of messages for it. You can trivially aim it at file systems, message queues, databases, web services and all manner of other sources to grab your data for you, and you can change your mind about what that source is, without having to rewrite most of your client code.

For a simple sequential Pipeline, my goto would be Apache Camel. As soon as you want complexity its either Apache Nifi or a micro service architecture.

🐪 Apache Camel : Camel JBang, A JBang-based Camel app for easily running Camel routes.

Apache Camel

So, my advice is this. Expand your knowledge. Pursue higher education on topics you are familiar with, but also explore topics you are not. Read documentation, but question it. I just found out about something called Apache Camel today that I am excited to read up on. Why is it better than Spring? Is it really? What's happening here? This is always what excites me as a developer and engineer. There is so much to learn.

The “restart from where it failed”-aspect was a big reason for why I made Mats3. It is message-based, async, transactional, staged stateless services, or message-oriented asynchronous RPC. Due to the transactionality, and the “state lives on the wire”, if a flow fails, it can be restarted from where it left off.

https://mats3.io

I am truly finding it hard to explain it. I have tried along a dozen angles. I actually think it is a completely new concept - and that might be the problem.

There is an illustration on the front-page: https://mats3.io/

Here's a set of small answers to "What is Mats?": https://github.com/centiservice/mats3/blob/main/README.md#wh...

Here's a way to code up Mats3 endpoints using JBang and a small toolkit which makes it extremely simple to explore the ideas: https://github.com/centiservice/mats3/blob/main/README.md#wh...

If you read these and then get it, I would be extremely happy if you gave me a sentence or paragraph that would have led you to understanding faster!

The use of JMS is just a transport. I could really have used anything, incl. any MQ, or ZeroMQ, or plain TCP - or just a shared table in a database.

Wrt. WebSockets, that is a transport typically between a server, and a end-user client, e.g. an iOS App. Actually, there's also a "sister project", MatsSockets, that bring the utter async-ness of Mats3 all the way out to the client, e.g. a webpage or an app. https://matssocket.io/

NATS is just a message queue, with some ability to orchestrate. I do not like this concept of orchestration as an external service, that is one of the founding ideas of Mats3: Do the orchestration within each service, as you would do if you employed REST as the ISC mechanism.

Read more about mats3 here: https://mats3.io/

I've made a Java library to facilitate the latter. https://mats3.io/ - you can start reading here: https://mats3.io/docs/message-oriented-rpc/, or test out some code right away, using JBang, here: https://mats3.io/explore/jbang-mats/

I have explained about this on the frontpage of Mats3: https://mats3.io/, and more in-depth in the first step of the "Walkthrough": https://mats3.io/docs/message-oriented-rpc/ - and even more into it at "Rationale for Mats", here: https://mats3.io/background/rationale-for-mats/

JBang’s tagline: “Lets Students, Educators and Professional Developers create, edit and run self-contained source-only Java programs with unprecedented ease.”

Mats3’s tagline: “Message-Oriented Async RPC. Message-based Interservice Communication made easy! Naturally resilient and highly available microservices, with great DevX and OpsX.”

JBang is a cool "execute single Java source file with dependencies" solution, which offers a simple way to test new libraries. The article tries to showcase Mats3's core concepts through a series of JBang scripts.

To streamline the process, a small library called 'MatsJbangKit' has been developed, which not only takes care of pulling up the Mats infrastructure but also depends on all the necessary dependencies. This means users only need to reference this single library in their JBang scripts. The aim is to pique curiosity and inspire further exploration of Mats3 and its potential.

If you like it, a star on Github would be much appreciated: https://github.com/centiservice/mats3

This is a "tack on"-tool to the otherwise fully async nature of Mats/messaging.

> For this to really work well, the message passing has to be integrated with the CPU dispatcher

It sounds like you are 100% set on speed. This is not really what Mats is after - it is meant as a inter-service communcation system, and IO will be your limiting factor at any rate. Mats sacrifices a bit of speed for developer ergonomics - the idea is that by easily enabling fully async development of ISC in a complex microservice system, you gain back that potential loss from a) actually being able to use fully async processing (!), and b) the inherent speed of messaging (it is at least as fast as HTTP, and you avoid the overhead of HTTP headers etc.

It is mentioned here, "What Mats is not": https://github.com/centiservice/mats3#what-mats-is-not