Senior Software Engineer at a tech services company with 501-1,000 employees
Dec 21, 2020
The feature that I've found most valuable is the replay. That is one of the most valuable in our business. We are business-to-business so replay was an important feature - being able to replay for 24 hours. That's an important feature.
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.
Senior Software Engineer at a tech services company with 501-1,000 employees
Dec 21, 2020
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.
Something else to mention is that we use Kinesis with Lambda a lot and the fact that you can only connect one Stream to one Lambda, I find is a limiting factor. I would definitely recommend to remove that constraint.
The services which are described in the documentation could use some visual presentation because for someone who is new to the solution the documentation is not easy to follow or beginner friendly and can leave a person feeling helpless.
One area for improvement in the solution is the file size limitation of 10 Mb. My company works with files with a larger file size.
The batch size and throughput also need improvement in Amazon Kinesis.
