Amazon SQS vs NSQ

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Amazon SQS

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NSQ

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Amazon SQS vs NSQ: What are the differences?

What is Amazon SQS? Fully managed message queuing service. Transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be always available. With SQS, you can offload the administrative burden of operating and scaling a highly available messaging cluster, while paying a low price for only what you use.

What is NSQ? A realtime distributed messaging platform. NSQ is a realtime distributed messaging platform designed to operate at scale, handling billions of messages per day. It promotes distributed and decentralized topologies without single points of failure, enabling fault tolerance and high availability coupled with a reliable message delivery guarantee. See features & guarantees.

Amazon SQS and NSQ can be primarily classified as "Message Queue" tools.

Some of the features offered by Amazon SQS are:

  • A queue can be created in any region.
  • The message payload can contain up to 256KB of text in any format. Each 64KB ‘chunk’ of payload is billed as 1 request. For example, a single API call with a 256KB payload will be billed as four requests.
  • Messages can be sent, received or deleted in batches of up to 10 messages or 256KB. Batches cost the same amount as single messages, meaning SQS can be even more cost effective for customers that use batching.

On the other hand, NSQ provides the following key features:

  • support distributed topologies with no SPOF
  • horizontally scalable (no brokers, seamlessly add more nodes to the cluster)
  • low-latency push based message delivery (performance)

"Easy to use, reliable" is the top reason why over 45 developers like Amazon SQS, while over 23 developers mention "It's in golang" as the leading cause for choosing NSQ.

NSQ is an open source tool with 15.5K GitHub stars and 2.04K GitHub forks. Here's a link to NSQ's open source repository on GitHub.

Lyft, SendGrid, and PedidosYa are some of the popular companies that use Amazon SQS, whereas NSQ is used by Stripe, Movable Ink, and Path. Amazon SQS has a broader approval, being mentioned in 381 company stacks & 101 developers stacks; compared to NSQ, which is listed in 21 company stacks and 8 developer stacks.

Advice on Amazon SQS and NSQ
Pulkit Sapra
Needs advice
on
RabbitMQRabbitMQKubernetesKubernetes
and
Amazon SQSAmazon SQS

Hi! I am creating a scraping system in Django, which involves long running tasks between 1 minute & 1 Day. As I am new to Message Brokers and Task Queues, I need advice on which architecture to use for my system. ( Amazon SQS, RabbitMQ, or Celery). The system should be autoscalable using Kubernetes(K8) based on the number of pending tasks in the queue.

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Replies (1)
Anis Zehani
Recommends
KafkaKafka

Hello, i highly recommend Apache Kafka, to me it's the best. You can deploy it in cluster mode inside K8S, thus you can have a Highly available system (also auto scalable).

Good luck

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Meili Triantafyllidi
Software engineer at Digital Science · | 6 upvotes · 260.7K views
Needs advice
on
ZeroMQZeroMQRabbitMQRabbitMQ
and
Amazon SQSAmazon SQS

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

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Replies (2)
Shishir Pandey
Recommends
RabbitMQRabbitMQ

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.

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Kevin Deyne
Principal Software Engineer at Accurate Background · | 5 upvotes · 69.7K views
Recommends
RabbitMQRabbitMQ

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.

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MITHIRIDI PRASANTH
Software Engineer at LightMetrics · | 4 upvotes · 161.5K views
Needs advice
on
Amazon SQSAmazon SQS
and
Amazon MQAmazon MQ
in

I want to schedule a message. Amazon SQS provides a delay of 15 minutes, but I want it in some hours.

Example: Let's say a Message1 is consumed by a consumer A but somehow it failed inside the consumer. I would want to put it in a queue and retry after 4hrs. Can I do this in Amazon MQ? I have seen in some Amazon MQ videos saying scheduling messages can be done. But, I'm not sure how.

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Replies (1)
Andres Paredes
Lead Senior Software Engineer at InTouch Technology · | 1 upvotes · 128K views
Recommends
Amazon SQSAmazon SQS

Mithiridi, I believe you are talking about two different things. 1. If you need to process messages with delays of more 15m or at specific times, it's not a good idea to use queues, independently of tool SQM, Rabbit or Amazon MQ. you should considerer another approach using a scheduled job. 2. For dead queues and policy retries RabbitMQ, for example, doesn't support your use case. https://medium.com/@kiennguyen88/rabbitmq-delay-retry-schedule-with-dead-letter-exchange-31fb25a440fc I'm not sure if that is possible SNS/SQS support, they have a maximum delay for delivery (maxDelayTarget) in seconds but it's not clear the number. You can check this out: https://docs.aws.amazon.com/sns/latest/dg/sns-message-delivery-retries.html

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Pramod Nikam
Co Founder at Usability Designs · | 2 upvotes · 318.1K views
Needs advice
on
NSQNSQKafkaKafka
and
Apache ThriftApache Thrift

I am looking into IoT World Solution where we have MQTT Broker. This MQTT Broker Sits in one of the Data Center. We are doing a lot of Alert and Alarm related processing on that Data, Currently, we are looking into Solution which can do distributed persistence of log/alert primarily on remote Disk.

Our primary need is to use lightweight where operational complexity and maintenance costs can be significantly reduced. We want to do it on-premise so we are not considering cloud solutions.

We looked into the following alternatives:

Apache Kafka - Great choice but operation and maintenance wise very complex. Rabbit MQ - High availability is the issue, Apache Pulsar - Operational Complexity. NATS - Absence of persistence. Akka Streams - Big learning curve and operational streams.

So we are looking into a lightweight library that can do distributed persistence preferably with publisher and subscriber model. Preferable on JVM stack.

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Replies (1)
Naresh Kancharla
Staff Engineer at Nutanix · | 4 upvotes · 315.5K views
Recommends
KafkaKafka

Kafka is best fit here. Below are the advantages with Kafka ACLs (Security), Schema (protobuf), Scale, Consumer driven and No single point of failure.

Operational complexity is manageable with open source monitoring tools.

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