Smack
Apache Camel
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Smack | Apache Camel | |
---|---|---|
2 | 21 | |
2,366 | 5,308 | |
0.1% | 1.1% | |
8.5 | 10.0 | |
3 days ago | about 15 hours ago | |
Java | Java | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Smack
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No XEP-0333 Chat Markers in XMMPP Openfire backend - how did you solve it?
Is this really impossible without Chat Markers? Do you suggest we switch the server stack to something else? eg. Smack seems to have some support
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Zoom: Remote Code Execution with XMPP Stanza Smuggling
https://github.com/igniterealtime/Smack/blob/master/smack-xm...
I don't see any opportunity not to block when calling "next"
Apache Camel
- Show HN: Winglang – a new Cloud-Oriented programming language
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Ask HN: What is the correct way to deal with pipelines?
"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.
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Is there something like airflow but written in Scala/Java?
Apache Camel Apache Nifi Spring Cloud
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Why messaging is much better than REST for inter-microservice communications
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/
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Can I continuously write to a CSV file with a python script while a Java application is continuously reading from it?
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.
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S3 to S3 transform
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.
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🗞️ We have just released our JBang! catalog 🛍️
🐪 Apache Camel : Camel JBang, A JBang-based Camel app for easily running Camel routes.
- 7GUIs of Java/Object Oriented Design?
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System Design: Enterprise Service Bus (ESB)
Apache Camel
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Advanced: Java, JVM and general knowledge
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.
What are some alternatives?
Conversations - Conversations is an open source XMPP/Jabber client for Android
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Xabber - Open-source XMPP client for Android
Apache Kafka - Mirror of Apache Kafka
yaxim - yaxim - a lean XMPP/Jabber client for Android
Apache Pulsar - Apache Pulsar - distributed pub-sub messaging system
Android-Paho-Mqtt-Service
Apache ActiveMQ Artemis - Mirror of Apache ActiveMQ Artemis
Nakadi - A distributed event bus that implements a RESTful API abstraction on top of Kafka-like queues
Spring Boot - Spring Boot
Aeron - Efficient reliable UDP unicast, UDP multicast, and IPC message transport