Production AI models are only as good as the freshness of the data fueling them. Whether dealing with anomaly detection, predictive maintenance, or IoT streams, traditional data stores often become bottlenecks under high-volume time-series ingestion. In this session, we will break down the key architectural challenges of processing millions of events per second - from memory layout and index structures to lock contention under extreme loads. Drawing from real-world lessons in building high-performance database engines, we will explore how to design a data layer that delivers ultra-low latency to AI algorithms without compromising consistency.