"The database that runs your app cannot be the database that analyzes your app". It's a hard lesson learned at scale. Early on, Postgres does it all. But as you hit massive scale, your analytics queries start killing your login APIs. This post breaks down the physics of Row-oriented (Couchbase) vs Column-oriented (ClickHouse) databases, and how to bridge them using Change Data Capture (CDC) for a robust, lag-free architecture.

CouchLens is a browser-based tool for analyzing Couchbase N1QL query performance. It parses system tables, extracts execution plans, and generates insights to help database administrators find performance bottlenecks without sending data to external servers. This post explains what it does, how to use it, and what features are coming.

Working with Couchbase for the past year and a half has been more than just learning a database. It has been an exercise in system thinking: seeing how indexes, queries, consistency, and durability interact, and how small design choices ripple through performance and reliability. This essay is my personal notebook from that journey. It is technically dense because Couchbase demands precision, but it is also reflective because the lessons extend beyond one database. Understanding how array indexes multiply entries, why compound index order matters, or how query consistency flags change latency is not just about Couchbase, it is about learning to think in terms of systems, trade‑offs, and consequences.

Bitmasking is one of those computer science tricks that feels like wizardry, until you realize it's just some clever shifting and binary math. This blog explores the idea, shows how we use it in Go, and why it's surprisingly useful when working with databases like Couchbase.