Event Sourcing

Deriving State from Events Event sourcing is the pattern where events are the source of truth and all state is derived by replaying them. Instead of storing 'account balance = $1,000,' you store every deposit and withdrawal event. The balance is computed by summing all events for that account. This is powerful but expensive. Replaying 10 years of events to compute a current balance is impractical. The solution: snapshots. Periodically compute the current state and save it. To get the balance, start from the last snapshot and replay only events since then. When Event Sourcing Makes Sense Event Sourcing in Data Engineering As a data engineer, you rarely build an event-sourced application. But you frequently consume event-sourced data. A payments team stores all transactions as events. Your p

About This Interactive Section

This section is part of the Event Streams 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.

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