We compared Apache Kafka and Amazon SQS based on our user's reviews in several parameters.
Apache Kafka stands out for its high scalability, fault-tolerant architecture, real-time data handling, stream processing, and data replication support. On the other hand, Amazon SQS is praised for its reliability, scalability, and ability to decouple application components seamlessly. While Apache Kafka offers easy integration with programming languages and frameworks, Amazon SQS provides efficient message handling for large volumes. Overall, Apache Kafka focuses on real-time data processing and stream processing, while Amazon SQS emphasizes reliable message handling and decoupling application components.
Features: Apache Kafka is highly valued for its high scalability, fault-tolerant architecture, and support for real-time data handling. It also offers seamless integration with programming languages and frameworks, and functionalities like stream processing and data replication. On the other hand, Amazon SQS is highly appreciated for its reliability, scalability, and the ability to decouple different components of an application, allowing for seamless integration and flexibility. It efficiently handles large volumes of messages.
Pricing and ROI: The available data did not provide any information about the setup cost for Apache Kafka. There were no details about the pricing, setup cost, and licensing for Amazon SQS from the reviewers., The ROI reviews for Apache Kafka are missing or unavailable, while for Amazon SQS, they are not available.
Room for Improvement: Apache Kafka: No specific feedback is available regarding areas for improvement. Amazon SQS: No specific feedback or suggestions have been provided for improvement.
Deployment and customer support: The given data source does not provide any user feedback specifically about the duration required to establish a new tech solution for Apache Kafka. Similarly, there is no specific information or quotes available regarding the setup time for Amazon SQS., Customer service and support for Apache Kafka cannot be compared as no reviews or feedback are available. Similarly, there are no reviews for customer service of Amazon SQS.
The summary above is based on 46 interviews we conducted recently with Apache Kafka and Amazon SQS users. To access the review's full transcripts, download our report.
"It is stable and scalable."
"One of the useful features is the ability to schedule a call after a certain number of messages accumulate in the container. For example, if there are ten messages in the container, you can perform a specific action."
"With SQS, we can trigger events in various cloud environments. It offers numerous benefits for us."
"SQS is very stable, and it has lots of features."
"I appreciate that Amazon SQS is fully integrated with Amazon and can be accessed through normal functions or serverless functions, making it very user-friendly. Additionally, the features are comparable to those of other solutions."
"The solution is easy to scale and cost-effective."
"We use SNS as the publisher, and our procurement service subscribes to those events using SQS. In the past, we relied on time-based or batch-based processes to send data between services on-premises. With SQS, we can trigger actions based on real-time changes in business processes, improving reliability."
"I am able to find out what's going on very easily."
"The open-source version is relatively straightforward to set up and only takes a few minutes."
"Deployment is speedy."
"It is a useful way to maintain messages and to manage offset from our consumers."
"Apache Kafka has good integration capabilities and has plenty of adapters in its ecosystem if you want to build something. There are adapters for many platforms, such as Java, Azure, and Microsoft's ecosystem. Other solutions, such as Pulsar have fewer adapters available."
"The most valuable feature is the messaging function and reliability."
"It's very easy to keep to install and it's pretty stable."
"I like Kafka's flexibility, stability, reliability, and robustness."
"With Kafka, events and streaming are persistent, and multiple subscribers can consume the data. This is an advantage of Kafka compared to simple queue-based solutions."
"Sending or receiving messages takes some time, and it could be quicker."
"There are some issues with SQS's transaction queue regarding knowing if something has been received."
"I do not think that this solution is easy to use and the documentation of this solution has a lot of problems and can be improved in the next release. Most of the time, the images in the document are from older versions."
"I cannot send a message to multiple people simultaneously. It can only be sent to one recipient."
"As a company that uses IBM solutions, it's difficult to compare Amazon SQS to other solutions. We have been using IBM solutions for a long time and they are very mature in integration and queuing. In my role as an integration manager, I can say that Amazon SQS is designed primarily for use within the Amazon ecosystem and does not have the same level of functionality as IBM MQ or other similar products. It has limited connectivity options and does not easily integrate with legacy systems."
"The tool needs improvement in user-friendliness and discoverability."
"Sometimes, we have to switch to another component similar to SQS because the patching tool for SQS is relatively slow for us."
"Be cautious around pay-as-you-use licensing as costs can become expensive."
"The management overhead is more compared to the messaging system. There are challenges here and there. Like for long usage, it requires restarts and nodes from time to time."
"Observability could be improved."
"Maintaining and configuring Apache Kafka can be challenging, especially when you want to fine-tune its behavior."
"Kafka's interface could also use some work. Some of our products are in C, and we don't have any libraries to use with C. From an interface perspective, we had a library from the readies. And we are streaming some of the products we built to readies. That is one of the requirements. It would be good to have those libraries available in a future release for our C++ clients or public libraries, so we can include them in our product and build on that."
"There have been some challenges with monitoring Apache Kafka, as there are currently only a few production-grade solutions available, which are all under enterprise license and therefore not easily accessible. The speaker has not had access to any of these solutions and has instead relied on tools, such as Dynatrace, which do not provide sufficient insight into the Apache Kafka system. While there are other tools available, they do not offer the same level of real-time data as enterprise solutions."
"The solution could always add a few more features to enhance its usage."
"It's not possible to substitute IBM MQ with Apache Kafka because the JMS part is not very stable."
"Too much dependency on the zookeeper and leader selection is still the bottleneck for Kafka implementation."
Amazon SQS is ranked 5th in Message Queue (MQ) Software with 13 reviews while Apache Kafka is ranked 1st in Message Queue (MQ) Software with 78 reviews. Amazon SQS is rated 8.2, while Apache Kafka is rated 8.0. The top reviewer of Amazon SQS writes "Stable, useful interface, and scales well". On the other hand, the top reviewer of Apache Kafka writes "Real-time processing and reliable for data integrity". Amazon SQS is most compared with Redis, Amazon MQ, Anypoint MQ, Oracle Event Hub Cloud Service and ActiveMQ, whereas Apache Kafka is most compared with IBM MQ, Red Hat AMQ, Anypoint MQ, PubSub+ Event Broker and VMware Tanzu Data Services. See our Amazon SQS vs. Apache Kafka report.
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We monitor all Message Queue (MQ) Software reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
