databases

9 posts

How Consistent Hashing Powers Distributed Systems

A deep dive into the algorithm that lets systems like Cassandra and Amazon's Dynamo route keys without reshuffling the entire keyspace when nodes come and go.

Asked at Amazon, Google, Meta +2

Jul 23, 2026·27 min read

Mediumhigh level design distributed systems databases

SQL vs NoSQL: Model the Access Pattern, Then Pick the Store

The choice isn't a religion — it's a consequence. Design how your data is read and written first, and the datastore that fits falls out of it. Pick the store first and you'll hand-join in application code for the next three years.

Asked at Amazon, Google, Netflix +3

Aug 8, 2026·15 min read

Mediumhigh level design distributed systems databases

Database Indexing: Why B-Trees Read Fast and LSM-Trees Write Fast

A missing index turns a one-user lookup into a scan of fifty million rows. Here's how the two great index families — B+ trees and LSM-trees — buy that lookup back, and what each one charges you for it.

Asked at Amazon, Google, Meta +3

Aug 8, 2026·13 min read

Mediumhigh level design distributed systems databases

Database Replication: Copies That Disagree With Each Other

Why the same query returns different answers on two servers a second apart — and the failover, lag, and conflict traps that turn 'just add a read replica' into a 3am incident.

Asked at Amazon, Google, Meta +3

Aug 8, 2026·15 min read

Hardhigh level design distributed systems databases

Database Sharding: When One Machine Stops Being Enough

Your 4 TB users table no longer fits — or no longer keeps up with writes — on a single node. Sharding is the answer, and the shard key you pick quietly decides everything that follows.

Asked at Amazon, Google, Meta +3

Aug 8, 2026·16 min read

Hardhigh level design distributed systems databases storage

Storage Engines: LSM-Trees vs B-Trees

Every database makes one foundational choice — how to lay bytes on disk. B-trees update in place; LSM-trees never overwrite, they append and compact. That single decision sets your write throughput, read latency, and space usage. Drive an LSM write path — memtable, flush, compaction — and see the tradeoff for yourself.

Asked at Google, Meta, Amazon +3

Aug 9, 2026·14 min read

System Design Case Studies3-part series

Mediumsystem design interview databases caching algorithms

Design a URL Shortener

The canonical system-design interview, built end to end: how tiny.co/aB3xK9 becomes a database lookup in single-digit milliseconds — base62, key generation, the read-heavy cache, and the scale math that makes 7 characters last a century.

Asked at Amazon, Google, Microsoft +2

Aug 9, 2026·20 min read

Mediumsystem design interview algorithms concurrency databases

Design a Distributed ID Generator

Auto-increment doesn't survive sharding, and random UUIDs wreck your database's index. How do you mint billions of unique, roughly time-sortable 64-bit IDs across a fleet with no coordinator? This is the Snowflake design — bit for bit.

Asked at Twitter, Instagram, Discord +2

Aug 9, 2026·16 min read

Hardsystem design interview databases algorithms concurrency

Design a Key-Value Store

The capstone that ties the whole series together: consistent hashing to place data, quorums to tune consistency, vector clocks to detect conflicts, and hinted handoff to stay writable through failure. This is Amazon's Dynamo, rebuilt from its four moving parts.

Asked at Amazon, Netflix, Uber +2

Aug 9, 2026·23 min read