Question 1

When would you choose SQL vs NoSQL?

Accepted Answer

**Target Audience:** Beginners to system design — you have used a spreadsheet or a database table; no database internals assumed.
**Difficulty:** Medium
**Verified with:** Node 22.22 and Python 3.12 (both print identical output).

> **How to read this doc:** Every idea is explained in plain language first, then tagged with `📌 Interview term:` so you also learn the exact words an interviewer expects. Behaviour shown comes from running the example; the **Verified** section quotes the full output.

Question 2

What is database sharding?

Accepted Answer

**Target Audience:** Beginners to system design who know what a database table is; no distributed-systems background assumed.
**Difficulty:** Medium
**Verified with:** Node 22.22 and Python 3.12 (both print identical output). Notion figures are cited from the Notion engineering blog; DynamoDB limits from the AWS DynamoDB developer guide.

> **How to read this doc:** Every idea is explained in plain language first, then tagged with `📌 Interview term:` so you also learn the words an interviewer e

Question 3

What is two-phase commit and its drawbacks?

Accepted Answer

**Target Audience:** Developers who know what a database transaction is and now meet data spread over several databases or services. No distributed-systems background assumed.
**Difficulty:** Medium
**Verified with:** Node 22.22 and Python 3.12 (both print identical output).

> **How to read this doc:** Every idea is explained in plain language first, then tagged with `📌 Interview term:` so you also learn the exact words an interviewer expects. All timings and counts come from running the examp

Question 4

What is a write-ahead log (WAL)?

Accepted Answer

**Target Audience:** Beginners to database internals — you know a database stores data on disk and that a server can crash; everything else is defined as we go.
**Difficulty:** Medium
**Verified with:** Node 22.22 and Python 3.12 (both print identical output). PostgreSQL settings were read with `SHOW` on a local PostgreSQL 16.15 server; SQLite behaviour was checked with SQLite 3.45.1 from Python.

> **How to read this doc:** Every idea is explained in plain language first, then tagged with `📌 I

Question 5

What is the difference between optimistic and pessimistic locking?

Accepted Answer

**Target Audience:** Beginners to databases and concurrency — you know what a row, a transaction and an `UPDATE` are; locking is built up from there.
**Difficulty:** Medium
**Verified with:** Node 22.22 and Python 3.12 (both print identical output). PostgreSQL defaults quoted below were read with `SHOW` on a local PostgreSQL 16.15 server; the SQL patterns are shown for illustration and were not executed in this run.

> **How to read this doc:** Every idea is explained in plain language first, th

Question 6

What is the saga pattern for distributed transactions?

Accepted Answer

**Target Audience:** Developers who build or interview for microservice back ends. You know what a database transaction is; no distributed-systems background assumed.
**Difficulty:** Medium
**Verified with:** Node 22.22 and Python 3.12 (both print identical output).

> **How to read this doc:** Every idea is explained in plain language first, then tagged with `📌 Interview term:` so you also learn the exact words an interviewer expects. All behaviour shown comes from running the example; the **V

Question 7

How would you design a distributed cache?

Accepted Answer

**Target Audience:** Intermediate — you know what a cache is and what a hash function does; distributed-systems vocabulary is defined as it appears.
**Difficulty:** Hard
**Verified with:** Node 22.22, Python 3.12, Go 1.24 and Java 21 (all four print identical output).

> **How to read this doc:** Every idea is explained in plain language first, then tagged with `📌 Interview term:` so you also learn the exact words an interviewer expects. Slot numbers, key movements and node loads come from runn

Question 8

How would you design Mint.com (personal finance aggregator)?

Accepted Answer

## Step 1: Use Cases, Constraints, Assumptions, Back-of-Envelope

### Use cases
We'll scope to handle only the core flows that expose the bottlenecks; everything else is deferred.

- **User** links bank — OAuth/Finicity/Plaid flow, store encrypted tokens, test connection.
- **Service** syncs transactions — scheduled fetch (hourly/daily), normalize categories, dedupe by fit_id.
- **User** reads dashboard — aggregated balances, trends, budgets, search over normalized ledger.
- **Service** alerts —

Question 9

Outbox pattern vs polling for CDC — how do you avoid dual-write failure?

Accepted Answer

**Target Audience:** Back-end developers who publish events from services that also own a database. You know what a database transaction and a message broker are; no prior knowledge of CDC assumed.
**Difficulty:** Hard
**Verified with:** Node 22.22 and Python 3.12 (both print identical output).

> **How to read this doc:** Every idea is explained in plain language first, then tagged with `📌 Interview term:` so you also learn the exact words an interviewer expects. All counts come from running t

Question 10

Exactly-once processing — can Kafka or SQS guarantee it?

Accepted Answer

**Target Audience:** Engineers who have used a queue or Kafka and heard "exactly-once" promised; everything from offsets to transactions is defined as we go.
**Difficulty:** Hard
**Verified with:** Node 22.22 and Python 3.12 (both print identical output). Kafka and SQS behaviour is from the Apache Kafka KIPs and documentation and the AWS SQS Developer Guide, checked in October 2026.

> **How to read this doc:** Every idea is explained in plain language first, then tagged with `📌 Interview term:

SYSTEM DESIGNDECODED.

Medium