We compared Confluent and Amazon Kinesis based on our user's reviews in several parameters.
Based on user reviews, Confluent is praised for its efficient handling of vast amounts of data, seamless integration with various systems, and strong customer support. In contrast, Amazon Kinesis is commended for its real-time data processing capabilities, flexibility in integration with other AWS services, and user-friendly pricing and licensing. Confluent users highlight the need for improved UI and setup simplification, while Amazon Kinesis users suggest better documentation, UI enhancements, and scalability improvements. Ultimately, both platforms have received positive ROI feedback, with users experiencing returns on their investments.
Features: Confluent's valuable features include efficient handling of vast amounts of data, seamless integration with external systems, and comprehensive monitoring and management capabilities. Amazon Kinesis, on the other hand, offers efficient real-time processing of high data volumes, flexible data streaming and processing options, easy integration with AWS services, and availability of various tools and APIs.
Pricing and ROI: The setup cost for Confluent's product has mixed sentiments from users, with some finding it manageable but others finding it complex. In contrast, users have positive feedback about the minimal and straightforward setup cost of Amazon Kinesis product., Confluent's product has received positive feedback for its strong return on investment. On the other hand, Amazon Kinesis offers significant ROI through cost savings, improved data processing efficiency, real-time analytics capabilities, scalability, and elasticity.
Room for Improvement: Confluent can improve its user interface and setup process, as well as provide better documentation. On the other hand, Amazon Kinesis needs enhancements in documentation, user interface, scalability, integrations, error handling, pricing, and customer support.
Deployment and customer support: User feedback on Confluent's tech solution indicates varying durations for deployment, setup, and implementation phases. In contrast, user feedback on Amazon Kinesis shows different timeframes for deployment and setup, emphasizing the need to consider them together or separately., Confluent's customer service is highly regarded for prompt and efficient support, while Amazon Kinesis is praised for outstanding assistance and representatives going above and beyond to address issues.
The summary above is based on 18 interviews we conducted recently with Confluent and Amazon Kinesis users. To access the review's full transcripts, download our report.
"The solution's technical support is flawless."
"Setting Amazon Kinesis up is quick and easy; it only takes a few minutes to configure the necessary settings and start using it."
"From my experience, one of the most valuable features is the ability to track silent events on endpoints. Previously, these events might have gone unnoticed, but now we can access them within the product range. For example, if a customer reports that their calls are not reaching the portal files, we can use this feature to troubleshoot and optimize the system."
"Great auto-scaling, auto-sharing, and auto-correction features."
"Its scalability is very high. There is no maintenance and there is no throughput latency. I think data scalability is high, too. You can ingest gigabytes of data within seconds or milliseconds."
"What I like about Amazon Kinesis is that it's very effective for small businesses. It's a well-managed solution with excellent reporting. Amazon Kinesis is also easy to use, and even a novice developer can work with it, versus Apache Kafka, which requires expertise."
"Amazon Kinesis has improved our ROI."
"The integration capabilities of the product are good."
"I find Confluent's Kafka Connectors and Kafka Streams invaluable for my use cases because they simplify real-time data processing and ETL tasks by providing reliable, pre-packaged connectors and tools."
"We mostly use the solution's message queues and event-driven architecture."
"The solution can handle a high volume of data because it works and scales well."
"Implementing Confluent's schema registry has significantly enhanced our organization's data quality assurance."
"The monitoring module is impressive."
"Kafka Connect framework is valuable for connecting to the various source systems where code doesn't need to be written."
"It is also good for knowledge base management."
"The design of the product is extremely well built and it is highly configurable."
"For me, especially with video streams, there's sometimes a kind of delay when the data has to be pumped to other services. This delay could be improved in Kinesis, or especially the Kinesis Video Streams, which is being used for different use cases for Amazon Connect. With that improvement, a lot of other use cases of Amazon Connect integrating with third-party analytic tools would be easier."
"In general, the pain point for us was that once the data gets into Kinesis there is no way for us to understand what's happening because Kinesis divides everything into shards. So if we wanted to understand what's happening with a particular shard, whether it is published or not, we could not. Even with the logs, if we want to have some kind of logging it is in the shard."
"We were charged high costs for the solution’s enhanced fan-out feature."
"Could include features that make it easier to scale."
"The solution has a two-minute maximum time delay for live streaming, which could be reduced."
"Kinesis Data Analytics needs to be improved somewhat. It's SQL based data but it is not as user friendly as MySQL or Athena tools."
"Kinesis is good for Amazon Cloud but not as suitable for other cloud vendors."
"The price is not much cheaper. So, there is room for improvement in the pricing."
"They should remove Zookeeper because of security issues."
"The formatting aspect within the page can be improved and more powerful."
"In Confluent, there could be a few more VPN options."
"Areas for improvement include implementing multi-storage support to differentiate between database stores based on data age and optimizing storage costs."
"It could be improved by including a feature that automatically creates a new topic and puts failed messages."
"The product should integrate tools for incorporating diagrams like Lucidchart. It also needs to improve its formatting features. We also faced issues while granting permissions."
"Confluence could improve the server version of the solution. However, most companies are going to the cloud."
"Confluent has a good monitoring tool, but it's not customizable."
Amazon Kinesis is ranked 1st in Streaming Analytics with 24 reviews while Confluent is ranked 4th in Streaming Analytics with 19 reviews. Amazon Kinesis is rated 8.0, while Confluent is rated 8.4. The top reviewer of Amazon Kinesis writes "Used for media streaming and live-streaming data". On the other hand, the top reviewer of Confluent writes "Has good technical support services and a valuable feature for real-time data streaming ". Amazon Kinesis is most compared with Azure Stream Analytics, Amazon MSK, Apache Flink, Google Cloud Dataflow and Apache Spark Streaming, whereas Confluent is most compared with Amazon MSK, Databricks, AWS Glue, Oracle GoldenGate and Fivetran. See our Amazon Kinesis vs. Confluent report.
See our list of best Streaming Analytics vendors.
We monitor all Streaming Analytics 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.
