Amazon SQS vs Gearman: What are the differences?
Developers describe Amazon SQS as "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. On the other hand, Gearman is detailed as "A generic application framework to farm out work to other machines or processes". 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.
Amazon SQS and Gearman can be categorized 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, Gearman provides the following key features:
- Open Source It’s free! (in both meanings of the word) Gearman has an active open source community that is easy to get involved with if you need help or want to contribute. Worried about licensing? Gearman is BSD
- Multi-language - There are interfaces for a number of languages, and this list is growing. You also have the option to write heterogeneous applications with clients submitting work in one language and workers performing that work in another
- Flexible - You are not tied to any specific design pattern. You can quickly put together distributed applications using any model you choose, one of those options being Map/Reduce
"Easy to use, reliable" is the primary reason why developers consider Amazon SQS over the competitors, whereas "Free" was stated as the key factor in picking Gearman.
Medium, Lyft, and Coursera are some of the popular companies that use Amazon SQS, whereas Gearman is used by Instagram, Hootsuite, and Grooveshark. Amazon SQS has a broader approval, being mentioned in 384 company stacks & 103 developers stacks; compared to Gearman, which is listed in 19 company stacks and 5 developer stacks.
What is Amazon SQS?
What is Gearman?
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In the beginning we thought we wanted to start using something like RabbitMQ or maybe Kafka or maybe ActiveMQ. Back then we only had a few developers and no ops people. That has changed now, but we didn't really look forward to setting up a queuing cluster and making sure that all works.
What we did instead was we looked at what services Amazon offers to see if we can use those to build our own messaging system within those services. That's basically what we did. We wrote some clients in Ruby that can basically do the entire orchestration for us, and we run all our messaging on both SNS and SQS. Basically what you can do in Amazon services is you can use Amazon Simple Notification Service, so SNS, for creating topics and you can use queues to subscribe to these topics. That's basically all you need for a messaging system. You don't have to worry about scalability at all. That's what really appealed to us.
This isn't exactly low-latency (10s to 100s of milliseconds), but it has good throughput and a simple API. There is good reliability, and there is no configuration necessary to get up and running. A hosted queue is important when trying to move fast.
Internal, distributed message queue. Main communication happens via port 4730 and consists of simple json messages. Completely independent of the main website back-end.
SQS is the bridge between our new Lambda services and our incumbent Rails applications. Extremely easy to use when you're already using other AWS infrastructure.
Primary message queue. Enqueueing operations revert to a local file-system-based queue when SQS is unavailable.