Why Migrations Break A migration that runs in 200ms on your local machine takes 30 minutes on the production table with 50 million rows. During those 30 minutes, your ALTER TABLE holds a lock that...

Why Caching Exists A single database query takes 5ms. A cache lookup takes 1ms. The difference seems small — but at 10,000 requests per second, that 4ms gap is 40 seconds of cumulative latency per...

Where We Are Post 1 built the WAL — every write is fsynced to disk before being acknowledged. Post 2 built the memtable — an in-memory skip list that keeps keys sorted and serves reads in O(log n)...

Where We Are In Part 1 we built a Write-Ahead Log. Every mutation — write or delete — is recorded to disk and fsynced before we acknowledge it to the caller. We have durability. What we do not ha...

Implementing a Write-Ahead Log in Go A Write-Ahead Log is the mechanism behind the D in ACID. Before any mutation reaches your data files, a record describing that mutation is written and fsynced ...

Introduction Your API receives a request. You need to send a confirmation email, resize an image, call a third-party webhook, and update an analytics counter. You could do all of that synchronous...

Introduction Your application writes a row. PostgreSQL says “committed.” The server loses power one millisecond later. When it comes back, is your row there? The answer is yes — and the reason i...

Introduction Your application has one user. Concurrency is not a problem. That user reads data, writes data, nothing conflicts with anything. Then you have ten thousand users. Two of them update ...

Introduction Your single database server handled your first 100,000 users just fine. Then you hit a million. Queries slowed down. Disk filled up. You threw more RAM at it. It helped — for a while....

Why B+ Trees Exist Your database has 50 million rows. You query by user ID. Without an index, the database reads every row until it finds yours. That’s a full table scan. It gets slower with every...