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."
"We use the tool in interface integrations."
"The solution is easy to scale and cost-effective."
"It's very quick and easy to build or set up Amazon SQS."
"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 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."
"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."
"Excellent speeds for publishing messages faster."
"This is a system for email and other small devices. There has been a relay of transactions continuously over the last two years it has been in production."
"Apache Kafka is scalable. It is easy to add brokers."
"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."
"The stability is very nice. We currently manage 50 million events daily."
"The valuable features are the group community and support."
"Resiliency is great and also the fact that it handles different data formats."
"I have seen a return on investment with this solution."
"Sending or receiving messages takes some time, and it could be quicker."
"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."
"Sometimes, we have to switch to another component similar to SQS because the patching tool for SQS is relatively slow for us."
"It would be easier to have a dashboard that allows us to see everything and manage everything since we have so many queues."
"There are some issues with SQS's transaction queue regarding knowing if something has been received."
"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 user interface is one weakness. Sometimes, our data isn't as accessible as we'd like. It takes a lot of work to retrieve the data and the index."
"In Apache Kafka, it is currently difficult to create a consumer."
"The ability to connect the producers and consumers must be improved."
"Too much dependency on the zookeeper and leader selection is still the bottleneck for Kafka implementation."
"The solution should be easier to manage. It needs to improve its visualization feature in the next release."
"It's not possible to substitute IBM MQ with Apache Kafka because the JMS part is not very stable."
"The manageability should be improved. There are lots of things we need to manage and it should have a function that enables us to manage them all cohesively."
"Managing Apache Kafka can be a challenge, but there are solutions. I used the newest release, as it seems they have removed Zookeeper, which should make it easier. Confluent provides a fully managed Kafka platform, in which the cluster does not need to be managed."
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.
See our list of best Message Queue (MQ) Software vendors.
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.