Real-time stream processing is growing exponentially in recent years and many developers are using containers on Kubernetes to deploy their real-time applications. Gathering insights from real-time data is a crucial step for any application that requires capturing and processing data in motion. To achieve this, SQL stream processing provides a solution to query data in motion, at rest, or a combination of both. However, achieving high-performance SQL streaming has many challenges such as speed and performance, scale, security, resilience, and most importantly, simplicity. This talk will address these challenges and will provide answers to achieving simple high-performance SQL stream processing in Kubernetes using the Hazelcast open-source platform. It will demonstrate best practices to quickly develop SQL stream processing pipelines and deploy them to Kubernetes using only configuration and minimal code. The source code will be available on Github.