Picking Batch or Streaming

Concepts covered: paBatchVsStreamingChoice

Vocabulary becomes useful when applied to a specific decision. The exercise below picks between batch and streaming for three small concrete cases. The cases are intentionally simple so the choice is visible. Real production decisions are messier, but the same questions apply: what does the consumer need, when do they need it, and what does each option cost. Case 1: A Marketing Team's Daily Signup Count The marketing team wants a chart of new signups by country, by day, for the trailing 30 days. The chart is read once a morning at the marketing standup. The numbers do not change after the day closes. The consumer is patient: yesterday's number is fine, today's morning number is a bonus. The freshness tier is 4 (daily). The right architecture is a nightly batch that aggregates the day's sig

About This Interactive Section

This section is part of the Batch vs Streaming: 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.