When customers were asking for an S3 connector, there were already several Kafka-to-S3 solutions out there at the time, so we had to decide whether to adopt an existing S3 connector, modify the Kafka Connect HDFS connector (as some developers attempted to do) or write a new connector from scratch.
We knew that our users needed three things from the connector:
1. Integration with the Kafka Connect API: Connect’s scaling and fault tolerance capabilities were important to have, and users didn’t want yet another system that they’d need to learn how to use, deploy and monitor.
2. Exactly once: Users didn’t want to waste expensive compute cycles on deduplicating their data. And no one likes missing events.
3. No extra dependencies: Especially dependencies on additional datastores. Kafka clients and the S3 SDK libraries should be all you need to get events from Kafka to S3. Simplicity rules, especially in a distributed systems world where simple is often the key to being reliable.
When we considered the existing connectors, we noticed that none of them delivered the reliability and exactly once capabilities we wanted. They treat S3 like it’s another file system—though it isn’t really. For example, S3 lacks file appends, it is eventually consistent, and listing a bucket is often a very slow operation.
Click through for a dive into what Confluent did and how it works.