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Beanstalkd vs ZeroMQ: What are the differences?
Data Structure: One key difference between Beanstalkd and ZeroMQ is their data structure. Beanstalkd is a simple queue system that stores jobs in a queue with priority levels, while ZeroMQ is a messaging library that allows various messaging patterns, including pub/sub, request/reply, and push/pull.
Messaging Patterns: Another significant difference is in the messaging patterns supported. ZeroMQ provides a wide range of messaging patterns, which can be customized for different applications, while Beanstalkd primarily focuses on providing a simple queue system for job processing with support for delayed and priority jobs.
Transport Layers: The transport layers used by Beanstalkd and ZeroMQ also differ. Beanstalkd operates over a TCP connection, while ZeroMQ can support multiple transport protocols such as TCP, IPC, and PGM, providing more flexibility and scalability options.
Language Support: When it comes to language support, ZeroMQ is designed to be language-agnostic, offering bindings for multiple programming languages, including C++, Python, and Java. On the other hand, Beanstalkd has limited language support, primarily focusing on client libraries for languages like Python and Ruby.
Scalability: In terms of scalability, ZeroMQ is known for its high scalability and performance, making it suitable for distributed systems and high-throughput applications. Beanstalkd, while efficient for its intended use cases, may have limitations in handling a large number of concurrent connections and scaling to very high loads.
Community and Support: ZeroMQ has a larger and more active community compared to Beanstalkd, leading to more robust documentation, community support, and ongoing development. This can be a crucial factor for choosing between the two solutions based on the level of community engagement and support available.
In Summary, Beanstalkd and ZeroMQ differ in data structure, messaging patterns, transport layers, language support, scalability, and community engagement and support.
Hi, we are in a ZMQ set up in a push/pull pattern, and we currently start to have more traffic and cases that the service is unavailable or stuck. We want to: * Not loose messages in services outages * Safely restart service without losing messages (ZeroMQ seems to need to close the socket in the receiver before restart manually)
Do you have experience with this setup with ZeroMQ? Would you suggest RabbitMQ or Amazon SQS (we are in AWS setup) instead? Something else?
Thank you for your time
ZeroMQ is fast but you need to build build reliability yourself. There are a number of patterns described in the zeromq guide. I have used RabbitMQ before which gives lot of functionality out of the box, you can probably use the worker queues example from the tutorial, it can also persists messages in the queue.
I haven't used Amazon SQS before. Another tool you could use is Kafka.
Both would do the trick, but there are some nuances. We work with both.
From the sound of it, your main focus is "not losing messages". In that case, I would go with RabbitMQ with a high availability policy (ha-mode=all) and a main/retry/error queue pattern.
Push messages to an exchange, which sends them to the main queue. If an error occurs, push the errored out message to the retry exchange, which forwards it to the retry queue. Give the retry queue a x-message-ttl and set the main exchange as a dead-letter-exchange. If your message has been retried several times, push it to the error exchange, where the message can remain until someone has time to look at it.
This is a very useful and resilient pattern that allows you to never lose messages. With the high availability policy, you make sure that if one of your rabbitmq nodes dies, another can take over and messages are already mirrored to it.
This is not really possible with SQS, because SQS is a lot more focused on throughput and scaling. Combined with SNS it can do interesting things like deduplication of messages and such. That said, one thing core to its design is that messages have a maximum retention time. The idea is that a message that has stayed in an SQS queue for a while serves no more purpose after a while, so it gets removed - so as to not block up any listener resources for a long time. You can also set up a DLQ here, but these similarly do not hold onto messages forever. Since you seem to depend on messages surviving at all cost, I would suggest that the scaling/throughput benefit of SQS does not outweigh the difference in approach to messages there.
Pros of Beanstalkd
- Fast23
- Free12
- Does one thing well12
- Scalability9
- Simplicity8
- External admin UI developer friendly3
- Job delay3
- Job prioritization2
- External admin UI2
Pros of ZeroMQ
- Fast23
- Lightweight20
- Transport agnostic11
- No broker required7
- Low level APIs are in C4
- Low latency4
- Open source1
- Publish-Subscribe1
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Cons of Beanstalkd
Cons of ZeroMQ
- No message durability5
- Not a very reliable system - message delivery wise3
- M x N problem with M producers and N consumers1
