February 25-27, 2026
Montreal, 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.

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Sherif Behna

Hikari Data inc.

As a data architecture and data integration specialist, I am currently working on leveraging Apache Spark and Databricks, along with Data Contracts and Data Products, to deliver value from data. I'm also a veteran Java and .net developer, but I recently converted to Python for all the data engineering goodness.

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