This post explores how to achieve exactly‑once semantics in Apache Pulsar by combining transactions, fencing, and failure recovery techniques for reliable streaming pipelines.
Learn how to implement Debezium-based change data capture pipelines that guarantee exactly-once state, handle schema evolution gracefully, and execute reliable backfills at scale.
A deep dive into Flink’s checkpointing mechanism, fault-tolerant state management, and practical patterns for building reliable streaming pipelines.
A deep dive into the architecture behind JetStream’s exactly-once semantics — covering Raft-replicated streams, per-consumer ack tracking, redelivery semantics, and the dedup window that ties it all together.
How Apache Flink coordinates checkpoints with sink writers via a two-phase commit protocol to deliver end-to-end exactly-once guarantees across Kafka, filesystems, and databases.