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  1. Stackups
  2. Utilities
  3. Background Jobs
  4. Message Queue
  5. ActiveMQ vs Amazon SQS

ActiveMQ vs Amazon SQS

OverviewDecisionsComparisonAlternatives

Overview

Amazon SQS
Amazon SQS
Stacks2.8K
Followers2.0K
Votes171
ActiveMQ
ActiveMQ
Stacks879
Followers1.3K
Votes77
GitHub Stars2.4K
Forks1.5K

ActiveMQ vs Amazon SQS: What are the differences?

ActiveMQ is an open-source message broker that supports multiple messaging protocols, while Amazon SQS (Simple Queue Service) is a fully managed message queuing service provided by AWS. Let's explore the key differences between them.

  1. Message Delivery Model: ActiveMQ follows a traditional message queue model, where the messages are stored in queues and clients consume them in a sequential order. On the other hand, Amazon SQS follows a distributed messaging model, where messages are automatically distributed among multiple queues and processing is parallelized. This provides better scalability and fault tolerance.

  2. Message Ordering: ActiveMQ guarantees the ordered delivery of messages within a single queue, ensuring that messages are consumed in the same order as they are produced. In contrast, Amazon SQS does not guarantee strict ordering of messages, as it distributes messages across different servers and processing can happen in parallel. However, you can use message groups in Amazon SQS to ensure ordering of messages within a specific group.

  3. Message Persistence: ActiveMQ stores messages in a persistent manner, ensuring that they are not lost even in the case of server failures. It provides options for different persistence stores, such as relational databases or file systems. On the other hand, Amazon SQS stores messages redundantly across multiple availability zones, providing durability and high availability. It does not provide direct control over the persistence of individual messages.

  4. Message Visibility: ActiveMQ allows consumers to acknowledge the receipt of messages, making them invisible to other consumers. This ensures exclusive processing of messages by a single consumer. In Amazon SQS, messages become invisible as soon as they are received by a consumer. However, if the consumer fails to process the message within a specified visibility timeout period, the message becomes visible again and can be consumed by another consumer.

  5. Message Size Limit: ActiveMQ has a limit on the maximum size of messages that can be processed. The limit is typically based on the underlying persistence store. Amazon SQS supports larger message sizes compared to ActiveMQ. The maximum message size in Amazon SQS is 256KB for standard queues and 2GB for FIFO queues.

  6. Message Delay: ActiveMQ does not provide a built-in delay mechanism for delivering messages. However, it can be achieved using custom code or frameworks built on top of ActiveMQ. In Amazon SQS, you can set a delay on individual messages, specifying the time to wait before making the message visible to consumers. This can be useful in scenarios where messages need to be processed after a specific delay.

In summary, ActiveMQ follows a traditional message queue model with strict ordering and more control over persistence and message visibility. Amazon SQS, on the other hand, follows a distributed messaging model with automatic distribution and parallel processing, providing scalability and high availability. It has features such as message groups, larger message size support, and a built-in delay mechanism.

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Advice on Amazon SQS, ActiveMQ

Pulkit
Pulkit

Software Engineer

Oct 30, 2020

Needs adviceonDjangoDjangoAmazon SQSAmazon SQSRabbitMQRabbitMQ

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.

474k views474k
Comments
Meili
Meili

Software engineer at Digital Science

Sep 24, 2020

Needs adviceonZeroMQZeroMQRabbitMQRabbitMQAmazon 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}|tool:1064| 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

500k views500k
Comments
MITHIRIDI
MITHIRIDI

Software Engineer at LightMetrics

May 8, 2020

Needs adviceonAmazon SQSAmazon SQSAmazon MQAmazon MQ

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.

303k views303k
Comments

Detailed Comparison

Amazon SQS
Amazon SQS
ActiveMQ
ActiveMQ

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.

Apache ActiveMQ is fast, supports many Cross Language Clients and Protocols, comes with easy to use Enterprise Integration Patterns and many advanced features while fully supporting JMS 1.1 and J2EE 1.4. Apache ActiveMQ is released under the Apache 2.0 License.

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.;Long polling reduces extraneous polling to help you minimize cost while receiving new messages as quickly as possible. When your queue is empty, long-poll requests wait up to 20 seconds for the next message to arrive. Long poll requests cost the same amount as regular requests.;Messages can be retained in queues for up to 14 days.;Messages can be sent and read simultaneously.;Developers can get started with Amazon SQS by using only five APIs: CreateQueue, SendMessage, ReceiveMessage, ChangeMessageVisibility, and DeleteMessage. Additional APIs are available to provide advanced functionality.
Protect your data & Balance your Load; Easy enterprise integration patterns; Flexible deployment
Statistics
GitHub Stars
-
GitHub Stars
2.4K
GitHub Forks
-
GitHub Forks
1.5K
Stacks
2.8K
Stacks
879
Followers
2.0K
Followers
1.3K
Votes
171
Votes
77
Pros & Cons
Pros
  • 62
    Easy to use, reliable
  • 40
    Low cost
  • 28
    Simple
  • 14
    Doesn't need to maintain it
  • 8
    It is Serverless
Cons
  • 2
    Has a max message size (currently 256K)
  • 2
    Difficult to configure
  • 2
    Proprietary
  • 1
    Has a maximum 15 minutes of delayed messages only
Pros
  • 18
    Easy to use
  • 14
    Open source
  • 13
    Efficient
  • 10
    JMS compliant
  • 6
    High Availability
Cons
  • 1
    Support
  • 1
    ONLY Vertically Scalable
  • 1
    Difficult to scale
  • 1
    Low resilience to exceptions and interruptions

What are some alternatives to Amazon SQS, ActiveMQ?

Kafka

Kafka

Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

RabbitMQ

RabbitMQ

RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.

Celery

Celery

Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well.

NSQ

NSQ

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.

ZeroMQ

ZeroMQ

The 0MQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. 0MQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more.

Apache NiFi

Apache NiFi

An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.

Gearman

Gearman

Gearman allows you to do work in parallel, to load balance processing, and to call functions between languages. It can be used in a variety of applications, from high-availability web sites to the transport of database replication events.

Memphis

Memphis

Highly scalable and effortless data streaming platform. Made to enable developers and data teams to collaborate and build real-time and streaming apps fast.

IronMQ

IronMQ

An easy-to-use highly available message queuing service. Built for distributed cloud applications with critical messaging needs. Provides on-demand message queuing with advanced features and cloud-optimized performance.

Apache Pulsar

Apache Pulsar

Apache Pulsar is a distributed messaging solution developed and released to open source at Yahoo. Pulsar supports both pub-sub messaging and queuing in a platform designed for performance, scalability, and ease of development and operation.

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