Kafka Streams, a component of Apache Kafka, has been utilized by Walmart to build a high-availability, low-latency customer data platform for applications such as fraud detection, which requires rapid data processing and stringent service level agreements. The platform faces challenges common in distributed systems, such as balancing consistency and availability, particularly during cloud environment disruptions and system patches. Enhancements like KIP-535 and KIP-562 have been implemented to allow state stores to serve data from standby servers during rebalancing, reducing downtime and improving load balancing. Additionally, KAFKA-9169 addresses bugs related to unnecessary restoration processes, further increasing system availability. These improvements enable Kafka Streams to move closer to replacing traditional databases by providing high availability and low latency, reducing the need for multiple event streaming engines and databases in application development. The advancements in Kafka Streams, including interactive queries and versioned key-value state stores, are part of its evolution to challenge traditional databases and streamline developer workflows.