Amazon Simple Queue Service (SQS) vs. Google Cloud Pub/Sub

If you are looking to build something that just requires a simple queue service (as the name implies) this is great for it. You might look elsewhere though if you get into more complicated needs. This is also very well suited if you are already using other services with AWS and intend to fully build whatever you are building in AWS. If you are looking for a mixed environment -- SQS is not for you

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If you want to stream high volumes of data, be it for ETL streaming or event sourcing, Google Cloud Pub/Sub is your go-to tool. It's easy to learn, easy to observe its metrics and scales with ease without additional configuration so if you have more producers of consumers, all you need to do is to deploy on k8s your solutions so that you can perform autoscaling on your pods to adjust to the data volume. The DLQ is also very transparent and easy to configure. Your code will have no logic whatsoever regarding orchestrating pubsub, you just plug and play. However, if you are not in the Google Cloud Pub/Sub environment, you might have trouble or be most likely unable to use it since I think it's a product of Google Cloud.

• It provides an always-available serverless queue for workflows or mission-critical processes.
• Is extremely low cost and overall costs to our environments have been negligible.

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• With a pub/sub architecture the consumer is decoupled in time from the publisher i.e. if the consumer goes down, it can replay any events that occurred during its downtime.
• It also allows consumer to throttle and batch incoming data providing much needed flexibility while working with multiple types of data sources
• A simple and easy to use UI on cloud console for setup and debugging
• It enables event-driven architectures and asynchronous parallel processing, while improving performance, reliability and scalability

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• Almost all of the functionality has been covered by SQS, but they could improve the throughput time.
• Also, they could provide built-in Cloud Watch, so that we can easily configure it without any external efforts.

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• Would be nice if the queue could be extended beyond 7 days.
• We found it a bit tricky replay unacknowledged messages when needed.

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It serves all of our purposes in the most transparent way I can imagine, after seeing other message queueing providers, I can only attest to its quality.

It is easy to create Google Cloud Pub/Sub topics from both Web Console and CLI commands.

Google Cloud Pub/Sub supports creation of one or more subscriptions.

By supporting a BigQuery Pub/Sub subscription to automatically write to a BigQuery table it simplifies development by avoiding implementation of a custom micro service for writes to BigQuery.

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I have never faced a single problem in 4 years.

It's very fast, can be even better if you use protobuf.

Online blogging and documentation for SQS is great. There are many examples of implementing it and if you look hard enough, more than likely there are examples that meet the exact case with which you are working

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They have decent documentation, but you need to pay for support. We weren't able to answer all our questions with the documentation and didn't have time to setup support before we needed it so I can't give it a higher rating but I think it tends to be a bit slow unless you're a GCP enterprise support customer.

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The most comparable products are RabbitMQ, and perhaps ActiveMQ. Until recently, AWS did not offer a managed ActiveMQ product. Running RabbitMQ will never be to my team's competitive advantage; we wanted a managed service.

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Having used Amazon Web Services SNS & SQS I can say that even if the latter may offer more features, Google Cloud Pub/Sub is easier to use. On the other hand, usage of SNS & SQS as well as documentation and troubleshooting is easier with the AWS solution. Since we are not using GCP only for Pub/Sub the choice depends on other variables.

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You can just plug in consumers at will and it will respond, there's no need for further configuration or introducing new concepts. You have a queue, if it's slow, you plug in more consumers to process more messages: simple as that.

• Positive impact - time allocation towards different features
• Negative impact - too many resources dedicated towards debugging
• Positive impact - less manual labor during testing

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• Increased Efficiency with reliable and Google managed services up all the time wit Disaster Recovery in place as well
• Definitely Lower costs being a cloud based solution and easier to setup
• Faster Project delivery and go to market plan for the business use cases basis this technology at the back end

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