Amazon Kinesis vs. jKool

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.

Incentivized

JKool is a decent tool for retrieving information regarding user engagement and customer feedback for your software products. With these information it's very valuable stepping stone for us to make future updates or produce new products. However, there are some downsides with jKool, two of which are there are too much clutter in the GUI and it takes sometimes to turn how things work.

Incentivized

• Processing huge loads of data
• Integrating well with IoT Platform on Amazon
• Integration with overall AWS Ecosystem
• Scalability

Incentivized

• Not a queue system, so little visibility into "backlog" if there is any
• Confusing terminology to make sure events aren't missed
• Sometimes didn't seem to trigger Lambda functions, or dropped events when a lot came in

Incentivized

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.

Incentivized

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.

Incentivized

No other product that I used is similar to jKool, it's unique product that have good amount of features that I would be opened to invest more in the future if time permit. It still has a long way to go and the first thing it can do is clean up it user interface to make it better.

Incentivized

• Caused us to need to re-engineer some basic re-try logic
• Caused us to drop some content without knowing it
• Made monitoring much more difficult
• We eventually switched back to SQS because Kinesis is not the same as a Queue system

Incentivized