Amazon SQS vs Kafka Manager: What are the differences?
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; Kafka Manager: A tool for managing Apache Kafka, developed by Yahoo. This interface makes it easier to identify topics which are unevenly distributed across the cluster or have partition leaders unevenly distributed across the cluster. It supports management of multiple clusters, preferred replica election, replica re-assignment, and topic creation. It is also great for getting a quick bird’s eye view of the cluster.
Amazon SQS and Kafka Manager 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, Kafka Manager provides the following key features:
- Manage multiple clusters
- Easy inspection of cluster state (topics, brokers, replica distribution, partition distribution)
- Run preferred replica election
Kafka Manager is an open source tool with 7.55K GitHub stars and 1.84K GitHub forks. Here's a link to Kafka Manager's open source repository on GitHub.
According to the StackShare community, Amazon SQS has a broader approval, being mentioned in 384 company stacks & 103 developers stacks; compared to Kafka Manager, which is listed in 8 company stacks and 5 developer stacks.
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What is Kafka Manager?
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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.
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.