NOTE: WILD now has a write-ahead log for durability, and the commentary below that states it's not durable no longer applies. It's safe to use if you can find a use case for it. Remember when we thought putting databases in RAM was revolutionary? Great performance,
I've been working on a complex multi-model database for a few weeks now, and recently I took time to simplify and test out an idea I had on a simple key-value database. I started with the basics: A hash table in memory, a simple append-only log for persistence
Have you ever looked at something and thought, "Yeah, that's the right way to do it"? Because that's how I felt when digging into the replication architecture of LibSQL when I was adding replication to Kevo. If you don't care about the
So I've been thinking a lot about database internals the past few weeks. For instance, how do these things actually work under the hood? I mean, we're all writing code that hammers these poor databases with concurrent requests, and somehow they don't explode into
Database architecture might seem like an an arcane art, but at its core, it's about solving a fundamental challenge: how to retrieve and store data efficiently. While you've likely heard of relational databases using B-trees (like PostgreSQL or MySQL), there is another architectural approach that excels