Stream Processing

Concepts covered: paStreamProcessing

What They Want to Hear 'Streaming processes each event as it arrives, continuously. I would use it when stale data directly costs money or breaks the user experience, like fraud detection or live driver tracking.' Then name the tools: Kafka is the message broker that holds events. Flink or Spark Streaming is the processor that acts on them. You do not need to know how to configure these tools. You need to know what role each plays. The Tools to Name-Drop

About This Interactive Section

This section is part of the How Data Moves: Beginner lesson on DataDriven, a free data engineering interview prep platform. Each section includes explanations, worked examples, and hands-on code challenges that execute in real time. SQL queries run against a live PostgreSQL database. Python runs in a sandboxed Docker container. Data modeling problems validate against interactive schema canvases. All content is framed around what data engineering interviewers actually test at companies like Meta, Google, Amazon, Netflix, Stripe, and Databricks.

How DataDriven Lessons Work

DataDriven combines four interview rounds (SQL, Python, Data Modeling, Pipeline Architecture) with adaptive difficulty and spaced repetition. Easy problems get harder as you improve. Weak concepts resurface until you master them. Your readiness score tracks progress across every topic interviewers test. Every lesson section ends with problems you solve by writing and running real code, not by picking multiple-choice answers.