Amazon Kinesis is a streaming analytics suite for data intake from video or other disparate sources and applying analytics for machine learning (ML) and business intelligence.
$0.01
per GB data ingested / consumed
Confluent
Score 7.4 out of 10
N/A
Confluent Cloud is a cloud-native service for Apache Kafka used to connect and process data in real time with a fully managed data streaming platform. Confluent Platform is the self-managed version.
Amazon Kinesis is a great replacement for Kafka and it works better whenever the components of the solution are AWS based. Best if extended fan-out is not required, but still price-performance ratio is very good for simplifying maintenance.
I would go with a different option if the systems to be connected are legacy, for instance in the case of traditional messaging clients.
If you have a need to stream data, real time or segmented structured data then Confluent is a great platform to do so with. You won't run into packet transfer size limitations that other platforms have. Flexibility in on-prem, cloud, and managed cloud offerings makes it very flexible no matter how you choose to implement.
The documentation was confusing and lacked examples. The streams suddenly stopped working with no explanation and there was no information in the logs. All these were more difficult when dealing with enhanced fan-out. In fact, we were about to abort the usage of Kinesis due to a misunderstanding with enhanced fan-out.
The support from the Confluent platform is great and satisfying. We have been working with Confluent for more than a year now. They sent out resident architects to help us set up Confluent cluster on our cloud and help us troubleshoot problems we have encountered. Overall, it has been a great experience working with the Confluent Platform.
The main benefit was around set up - incredibly easy to just start using Kinesis. Kinesis is a real-time data processing platform, while Kafka is more of a message queue system. If you only need a message queue from a limited source, Kafka may do the job. More complex use cases, with low latency, higher volume of data, real time decisions and integration with multiple sources and destination at a decent price, Kinesis is better.
For our use case it was very important that the technology we were working with fit into our Azure architecture, and met our data processing size requirements to stream data within certain SLAs. Confluent more than met our performance requirements and compared to the others scale options and cost to run it was more than financially viable as a platform solution to our global operations.
