The paper "Streams and Tables: Two Sides of the Same Coin" published by Confluent and Humboldt-Universität zu Berlin presents the Dual Streaming Model, which is the foundation of Kafka Streams' and KSQL's stream processing semantics. This model provides a natural way to cope with inconsistencies between physical and logical order of streaming data in a continuous manner, without explicit buffering and reordering. The model decouples handling of out-of-order data from latency concerns, offering a design space between processing cost, accepted latency, and result completeness for users. The adoption of Kafka Streams and KSQL among enterprises demonstrates the Dual Streaming Model's ability to solve real-world problems across industries.