Batch vs Streaming

Concepts covered: paBatchVsStreaming

The #1 Pipeline Interview Question This question is designed to test your judgment, not your knowledge. The interviewer describes a scenario and wants to see you reason through the decision, not recite definitions. Here is the framework that works every time: Step 1: Ask 'If this data is 1 hour old, does anyone lose money or make a bad decision?' If no, batch. Step 2: If yes, ask 'Does a 5-minute delay cause the same problem?' If 5 minutes is fine, micro-batch. If sub-minute matters, true streaming. Step 3: State the tradeoff. 'Streaming costs 3-5x more in compute and engineering time. The business value of freshness needs to justify that.' Practice Scenarios

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.