Amazon SQS Reviews

Our primary use case was to connect SQS with S3 so that we could count the number of downloads of our objects within S3. However, we had to switch to using the CloudFront URL instead. We initially used SQS to help in decoupling and to find the number of messages coming in.

The most valuable feature is the ability to decouple components. It is beneficial because our architecture usually has different components and the communication aspect of components is crucial. SQS is effective in decoupling or buffering to prevent overwhelming components in case there is increased traffic, aiding in the management of communication loads. By design, it is scalable, and its SAGRAM feature helps to lower loads during surges.

The primary issue was the increase in costs due to frequent polling for messages. The cost became an issue, leading us to consider other solutions.

We used SQS for a project, however, due to cost concerns, we had to switch to a different solution.

We did not encounter any challenges with the stability of SQS. The only challenge we faced was with the cost.

SQS is scalable. It is designed to handle varying loads well, with the SAGRAM feature assisting in managing and lowering loads during increased traffic.

Understanding the service requires prior knowledge, and we could not just use it directly. We needed to first understand the service itself for deployment.

The main challenge we encountered was related to the cost increase due to frequent polling for messages.

We switched from using SQS to CloudFront, as CloudFront was a better fit for our needs and was more cost-effective.

I would recommend SQS to others depending on their use case. 

Overall, I would rate SQS a nine out of ten.

We use Amazon SQS for notifying, queuing servers, queuing messages, and notifying the people for alerting systems. We have been using Amazon SQS in one of the projects for queuing messages. For alerting, we have production support where SQS is mostly used.

I have been using Amazon SQS for four to five years.

We had no issues with the solution’s stability.

Amazon SQS is highly scalable, both horizontally and vertically. We don't see any scalability issues with the solution. More than 500 users are using the solution in our organization.

I created a support ticket one or two years ago. The technical support team responded promptly and helped us with the issues. I am very much happy with the solution’s technical support. They are knowledgeable, understand our problem easily, and then figure out the issues.

On a scale from one to ten, where one is bad and ten is excellent, I rate the solution’s technical support nine and a half out of ten.

Positive

I've previously used Kafka, which is similar to Amazon SQS but not exactly the same feature-wise. Kafka has different storage functionality, which we don't have in Amazon SQS. I'd say Amazon SQS is the best solution for messaging service.

The solution's initial setup is easy. Compared to other complex services in AWS, Amazon SQS is simple to configure. It is also simple to provision through the console and through Terraform.

Compared to EC2 and other services, Amazon SQS' pricing is cheaper.

Anyone with a basic cloud experience can use the solution. I would recommend Amazon SQS for any support project that needs message queuing and faster and more reliable processing.

Overall, I rate the solution ten out of ten.

The tool helps to process events in a microservices cluster. We use it in the financial industry. 

I like how we can subscribe to multiple topics in Amazon SQS. It's also much simpler and quicker to set up than other solutions. It also supports patterns like Kafka and RapidMQ's fan-out pattern but with easier implementation.

Amazon SQS is costly. I think there could be improvements in how it facilitates comparisons between different AWS products. A calculator would be helpful. The calculator for Kafka is based on factors like throughput or storage used in the last month. In contrast, the calculator for Amazon SQS is based on the number of transactions processed. These different approaches make it challenging to compare them directly. I suggest AWS provide a straightforward calculator where I can input one aspect, and it calculates costs for multiple solutions. 

I have been working with the product for two years. 

I rate the product's stability a ten out of ten. 

I rate the solution's scalability a ten out of ten. My company has 100 users. 

I rate the solution's deployment ease an eight out of ten. Its deployment is generally quick, but it involves considerations around security, which are essential for DevOps teams. Typically, it takes about one week for deployment. However, if I handled it for my project personally, the deployment time would likely be shorter.

I rate the tool's pricing a nine out of ten. 

We manage and monitor our Amazon SQS performance and costs using DataOps. It helps us with intuitive data. Transitioning from our legacy tools to Amazon SQS would be beneficial because it's simple to set up and can serve as a pilot for our approach.

I rate the overall product an eight out of ten. 

We use Amazon SQS for triggering other resources, such as Lambda, API Gateway, EC2 instances, and various tasks running inside different compute services. 

It's primarily used for queuing different tasks, alerting, and monitoring pipelines. Additionally, it is used for message distribution.

All Amazon Web Services resources are easy to configure. The configuration process is straightforward, making it easy to use. It's easy to get started with it.

There is room for improvement in all the resources. That said, it's currently pretty good. For example, improvement is needed in terms of troubleshooting and logs, as there is not much logging in SNS and SQS services. More specific logs would be helpful, as it's hard to troubleshoot without them.

I've been using it for quite a while, about four years.

Stability-wise, it's pretty good. It doesn't really break down, but it does freeze sometimes. However, the freezing is not that significant.

It is very scalable. Scalability-wise, I would give it a ten out of ten.

Personally, it's pretty good because, from my workplace, we receive special support. However, for the general public, it's not as good. The more you pay, the more support you get.

Neutral

I previously used both cloud and on-prem solutions. Of course, cloud is better than on-prem since there's no maintenance, but it comes at a cost.

It is expensive. The cloud is expensive.

I would recommend this product to bigger businesses.

I'd rate the solution nine out of ten.

Amazon SQS is used when the need arises to publish a message. This could be a natural message or a message to a service to execute a process. The consumer, which is usually a service, will catch it, consume it, and execute the process based on the message that is passed to the queue. This describes the general concept of our use case.

Amazon SQS helps process all the requests that come from the clients, and it enhances the client-side performance, making it faster. It ensures data is processed correctly with no data loss, especially with the Dead Letter Queue (DLQ) feature. This feature ensures that even if a message is not processed properly, it can be reprocessed later on.

The dead-letter queue is very helpful in maintaining the messages that come into the queue. It allows the consumer to process it again later when it is available, preventing the queue from being overlooked when the same message has been retried more than the specified attempts.

There could be improvements in the UI for security and scalability. Initially, I struggled to understand the scalability and get the general gist of how it works, but over time, it became clearer.

I have been working with Amazon Suite for a couple of months now.

The stability of Amazon SQS is really high, and I would rate it a nine out of ten. The stability ensures the data is processed correctly without any loss.

The scalability is pretty good, and I rate it around nine out of ten. It is possible to configure Amazon SQS to have several queues that may serve the same line but are divided into several consumers.

Currently, I haven't communicated with technical support for Amazon SQS since I haven't faced any specific problems requiring their support.

Positive

There was no previous solution before Amazon SQS.

The initial setup was mostly straightforward. I would rate my experience with it a nine. The problem was not with the configuration but with understanding the AWS implementation.

Only I was needed for the deployment since it was straightforward.

Amazon SQS contributes greatly to processing client requests, improves client-side performance, and maintains a high level of satisfaction for the consumers.

The pricing is rather affordable, and I would rate it at two to three out of ten, with ten being the most expensive.

I haven't evaluated alternate solutions for the use case of SQS.

I'd advise new users to look at the documentation and try to understand the basic queue and the implementation in Amazon SQS.

I'd rate the solution nine out of ten.

We use Amazon SQS for an asynchronous solution. We receive data through API calls, which we process and log to our database. To avoid doing this during the API call, we offload it to Amazon SQS. We have a service that monitors Amazon SQS to process the data in the background.

It helps with high volumes of data on the API, preventing us from doing too much processing for every API call. By using Amazon SQS as a holding area, we process data in the background, which does not affect the user experience on the front end.

Amazon SQS is reliable, with no issues to date. It handles its load well, and the graphs for monitoring are good. It offers durable storage, reducing data loss. The messages remain until processed and deleted, with a retention period of a maximum of 14 days.

It would be beneficial to have the ability to peek at messages currently in Amazon SQS without needing to monitor incoming messages. Additionally, when using Azure, I could look at messages while they were there. Such a feature would be useful in Amazon SQS as well.

I have used Amazon SQS for about two years now.

Amazon SQS is stable and handles its load effectively.

While Amazon SQS itself is not scalable, it supports scalability. It acts as a holding area between high volumes of messages, allowing us to scale and receive more messages without worrying about whether Amazon SQS can handle it.

I have not needed to escalate any issues to Amazon SQS customer support. It has been reliable without any need for assistance.

Positive

I have used Azure queues and Azure services. Azure allowed me to see the messages in the queue, which I found beneficial. However, Amazon SQS can store more messages at a time than Azure.

The initial setup was fairly straightforward.

From a programming and reliability standpoint, Amazon SQS is a good part of the infrastructure. It saves a lot of headaches and helps maintain system integrity.

The pricing and licensing details are abstracted from me, so I have not looked into them.

I have considered Azure queues and Azure services.

Using queues in an infrastructure is a good idea for certain scenarios. If you're going to use AWS and need queues, then Amazon SQS is the solution. I would recommend its use if you have simple enough needs.

I'd rate the solution eight out of ten.

The tool I use to transform and move data can read the entries from Amazon SQS. For example, to start some workflow orchestration, it checks Amazon SQS, reads new messages from it, and then runs some transformation. My responsibility was setting up the new SQS, setting up the right policies, adding some text, and allowing communication.

It's very quick and easy to build or set up Amazon SQS. It's a very stable solution, and we have never faced any downtime issues.

Sending or receiving messages takes some time, and it could be quicker.

I have been using Amazon SQS for one year.

I rate the solution ten out of ten for stability.

Around 500 users are using the solution in our organization.

I rate Amazon SQS ten out of ten for scalability.

The solution’s initial setup is straightforward.

Beginners can very easily set up Amazon SQS. It requires just a few clicks and then some permissions. The solution can be installed in 15 minutes.

Amazon SQS is moderately priced.

Users need to check the number of messages. Since the solution works on a pay-as-you-go model, it could be expensive if the number of messages is very large.

Overall, I rate Amazon SQS a nine out of ten.

We have recently started using Amazon SQS and we are in the R&D phase. We want to see how resilient the solution is. We use Amazon SQS for integration purposes between our different applications.

The most valuable feature of Amazon SQS is the interface.

I have been using Amazon SQS for approximately 

Amazon SQS is stable from the usage that we have had so far.

The scalability of the solution is good. We can scale it to different regions and deploy it within Amazon AWS.

I have not used the support from Amazon SQS.

We previously were using ActiveMQ and we had to manage it manually on our on-premise server.  We have seen that a lot of times the messaging queuing service stopped responding or we had to restart the server or the services themselves on the server. This is the reason we are switching to Amazon SQS.

Amazon SQS is well integrated with Amazon AWS which is helpful if it is needed to be scaled. ActiveMQ is open-source and free to use but it is not resilient or dependable. It stops working at times and you have to manage the server yourself. Amazon SQS is serverless, you don't have to manage the server, you only have to manage the permissions.

The initial setup of Amazon SQS is in the middle range of difficulty. You need to learn Amazon AWS and know how to navigate, create resources, and structures, and provide rules.

The pricing of Amazon SQS is reasonable. The first million requests are free every month, and after, it's cost 40 cents for every million requests. There are not any additional fees.

This is a free-to-use solution for somebody who wants to do 1 million requests, and this is sufficient for any application at a small organization. It's cost-effective, reliable, and easily scalable.

I rate Amazon SQS an eight out of ten.