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.
"There is no setup just some easy configuration required."
"The solution is easy to scale and cost-effective."
"The libraries that connect and manage the queues are rich in features."
"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."
"I am able to find out what's going on very easily."
"It is stable and scalable."
"We use the tool in interface integrations."
"The use of Kafka's logging mechanism has been extremely beneficial for us, as it allows us to sequence messages, track pointers, and manage memory without having to create multiple copies."
"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."
"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."
"The most valuable features are the stream API, consumer groups, and the way that the scaling takes place."
"Excellent speeds for publishing messages faster."
"Kafka, as compared with other messaging system options, is great for large scale message processing applications. It offers high throughput with built-in fault-tolerance and replication."
"Robust and delivers messages quickly."
"Apache Kafka is scalable. It is easy to add brokers."
"Sending or receiving messages takes some time, and it could be quicker."
"It would be easier to have a dashboard that allows us to see everything and manage everything since we have so many queues."
"The solution is not available on-premises so that rules out any customers looking for the messaging solution on-premises."
"The tool needs improvement in user-friendliness and discoverability."
"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."
"There are some issues with SQS's transaction queue regarding knowing if something has been received."
"Sometimes, we have to switch to another component similar to SQS because the patching tool for SQS is relatively slow for us."
"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."
"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."
"Some vendors don't offer extra features for monitoring."
"Too much dependency on the zookeeper and leader selection is still the bottleneck for Kafka implementation."
"I would like to see an improvement in authentication management."
"Apache Kafka can improve by adding a feature out of the box which allows it to deliver only one message."
"Data pulling and restart ability need improving."
"Apache Kafka has performance issues that cause it to lag."
"An area for improvement would be growth."
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.
