As enterprise streaming adoption accelerates, more teams are turning to real-time processing to support operational workloads that require sub-second response times. To address this need, Databricks introduced Project Lightspeed in 2022, which recently delivered Real-Time Mode in Apache Spark™ Structured Streaming. This new mode achieves consistent p99 latencies under 300ms for a wide range of stateless and stateful streaming queries. In this session, we’ll define what constitutes an operational use case, outline typical latency requirements and walk through how to meet those SLAs using Real-Time Mode in Structured Streaming.

Real-time mode is a new low-latency execution mode for Apache Spark™ Structured Streaming. It can consistently provide p99 latencies less than 300 milliseconds for a broad set of stateless and stateful streaming queries. Our talk focuses on the technical aspects of making this possible in Spark. We’ll dive into the core architecture that enables these dramatic latency improvements, including a concurrent stage scheduler and a non-blocking shuffle. We’ll explore how we maintained Spark’s fault-tolerance guarantees, and we’ll also share specific optimizations we made to our streaming SQL operators. These architectural improvements have already enabled Databricks customers to build workloads with latencies up to 10x lower than before. Early adopters in our Private Preview have successfully implemented real-time enrichment pipelines and feature engineering for machine learning — use cases that were previously impossible at these latencies.