System design vs SQL syntax interviews
A SQL syntax interview asks for a specific query or an explanation of what one returns. A system design interview asks how an entire pipeline should be architected — how data flows between systems, where it could break, and what a given design decision costs in complexity, latency, or money. SQL shows up as one tool for expressing parts of the answer, not as the entire subject being tested.
CDC design questions
Sample question: "A source system is a transactional database with roughly 10 million row changes per day, and downstream consumers need updates within 5 minutes. How would you design change capture for this?"
A strong answer names log-based CDC as the fit here — 5-minute latency and 10M daily changes rule out slow, high-overhead polling, and log-based capture reads the database's transaction log directly without adding write-path overhead to the source system. The answer should also cover how captured changes get applied downstream, typically via an idempotent MERGE, and should reference concrete mechanics (see Change Data Capture (CDC) Explained) rather than only naming a vendor tool.
Schema evolution design questions
Sample question: "The upstream team says they're renaming a column next sprint. How does your pipeline handle that without breaking?"
A strong answer separates the three failure modes: an added column is a non-event if the pipeline uses explicit column lists rather than SELECT *; a dropped or renamed column needs a pre-flight schema check that alerts clearly rather than letting the main pipeline query fail cryptically; and a rename specifically benefits from a transition window — supporting both the old and new column name temporarily — instead of an instant cutover that breaks every downstream consumer at once.
Cost tradeoff questions
Sample question: "Would you use a full reload or incremental load for a 2-billion-row fact table updated hourly?"
A strong answer ties the decision to the actual cost mechanism of the platform in question: reloading 2 billion rows hourly means re-scanning or re-processing the entire table every run, which on a byte-scanned or credit-per-second billing model compounds quickly, whereas incremental loading via a watermark keeps each run's cost proportional to the hour's actual change volume — at the cost of more implementation complexity and the need to handle late-arriving data correctly.
How to structure a strong answer
- State the design choice explicitly before diving into implementation detail — a graders should be able to identify the recommendation in the first sentence.
- Justify with the specific constraints given in the question (volume, latency, existing tooling) rather than a generic textbook answer.
- Name the failure modes the design needs to handle and how it handles them.
- Connect to cost or complexity tradeoffs explicitly, rather than presenting the design as strictly superior with no downsides.
Common mistakes
- Jumping straight to naming a tool (a specific vendor product) instead of explaining the underlying approach and why it fits.
- Ignoring the specific numbers given in the question — volume and latency requirements should visibly shape the answer.
- Presenting a design with no tradeoffs, which reads as not having considered alternatives.
- Treating cost as an afterthought rather than a first-class factor in the design decision.
Key takeaways
- System design interviews test architecture reasoning, not SQL syntax recall.
- CDC design questions expect a justified approach choice (query/trigger/log-based) tied to stated volume and latency constraints.
- Schema evolution questions expect separate handling for added, dropped, and renamed columns, with a transition window for renames.
- Cost questions expect the answer tied to the actual billing mechanism of the platform, not a vague "it's cheaper" claim.
- A strong answer states the choice, justifies it with given constraints, names failure modes, and is explicit about tradeoffs.