SocketCluster VS Apache Camel

Recently, I added an AI-generated soundtrack to my open source project's home page https://socketcluster.io/

It seems unconventional at first but I distinctly remember about a decade ago when Adobe Flash was still broadly supported, many Flash websites had soundtracks. I think the reason why regular HTML websites didn't have them was because it was difficult to implement and internet was much slower so they had to be streamed in a special way.

If redis doesn't satisfy your requirements or you're unable to make it work using adaptor, SocketCluster is a great package for this https://socketcluster.io/

Interesting how this feature set is pretty much exactly the same as offered by SocketCluster https://socketcluster.io/

This resonates with me 100%. Every bit of unhappiness I've felt in my career so far has been caused by a bad manager. The main issue for me has been the final point you mentioned about "Imposed artificial limitations" - I cannot tell you the number of times that I've been forced to use an inefficient tool or do something in a sub-optimal or downright incorrect way (knowing that it would have to be re-written later) by a bad manager... In some companies, it was a daily occurrence; that's why I never stayed at a single company for longer than 2 years. It's almost impossible to find a company that lets me implement things correctly.

Thankfully, nobody could constrain me in my open source work. I (with the help of community members) built:

- SocketCluster (https://socketcluster.io/): A distributed pub/sub framework.

- Capitalisk (https://capitalisk.com/): A lightweight quantum-resistant blockchain which is less than 5K lines of code.

- LDEX (https://ldex.trading/): A deterministic decentralized exchange (DEX) which can work with many different blockchain protocols. It's less than 4K lines of code in total and only has 3 small third-party dependencies (including sub-dependencies).

The two best lightweight solutions I have worked with are SocketCluster and NATS. SocketCluster is used to build out a custom backend that scales very well. NATS would be used as a central pub/sub system. If you need queueing, you'll need to add additional services like Redis.

In the homepage for SocketCluster it is mentioned that it is a Highly scalable pub/sub and RPC framework optimized for async/await. However in the documentation I have not found anything related to RPC. Am I interpreting anything wrong here?

At the time of writing, SocketCluster has almost 6k stars on GitHub and 7k downloads on npm weekly,

SocketCluster is a framework which allows you to use the WebSocket protocol the transmit between its backend API and client library. The client can be used both on a backend (E.g. a Raspberry pi) or frontend application.

"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.