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Kafka Streams uses local state for quick data access and changelogs for recovery.

Older offsets can overwrite newer ones in Kafka if not handled properly.

Kafka consumer reprocessing involves safely replaying events to correct system states.

Apache Kafka is a system for managing large volumes of events efficiently.

Kafka consumers can fetch data in batches to improve throughput and reduce latency.

Elasticsearch Data Streams simplify time-series data management with one name for many indices.

Kafka consumers can use multiple threads to speed up message processing, but it complicates ordering and offset management.

You can replay Kafka events safely by separating live and replay processes.