25 au 27 février, 2026
Montréal, Canada
Real-Time Streaming Showdown: Apache Spark and Apache Flink
Real-time data processing and analytics is more and more a requirement for modern applications. But how do you choose between Apache Spark and Apache Flink for streaming workloads? This talk dives into their architectures, trade-offs, and real-world use cases. We compare Spark Structured Streaming (micro-batching, ease of use) vs. Flink’s native streaming (low latency, stateful processing), looking at their features, performance and ecosystem.
Sherif Behna
SHB Informatique inc.
With a rich technical background, I am currently working on leveraging Big Data, Apache Spark, and Databricks to deliver value from data using the combination of Big Data, Machine Learning and Agile principles.
My professional journey reflects a commitment to continuous improvement and strategic transformation within the tech landscape. Among others, I focus on Domain Driven Design, Clean Code, MLOps, DevOps and Developer Experience (DUX), to develop high-quality, resilient systems.
