I spent two weeks setting up Elasticsearch for a project that had maybe 50,000 rows. Two weeks. Index mappings, JVM tuning, cluster config, and it still crashed on startup half the time. Then I deleted the whole thing and used PostgreSQL built-in full-text search instead. Took an afternoon. Same
I avoided JSONB for years ( like, actual years ). Not because I didn't know it existed, but because every time I reached for it, someone would say "just use a separate table" and I'd back off. Turns out, they were wrong. Not always wrong, but
I've written slow queries. You've written slow queries. We all pretend EXPLAIN ANALYZE is fine and then close the tab. But at some point you hit a table with 5 million rows and suddenly your app feels like it's running on a potato. Indexes
I stored JSON in PostgreSQL for two years before I realized I was doing it wrong. I mean, I had a column called metadata typed as TEXT. I was stringifying before insert and parsing after select. It worked. It was also slow, unqueryable, and frankly embarrassing. JSONB fixes all of
I keep underestimating SQLite. Every time I reach for PostgreSQL or MySQL for a new project, I stop and think: does this actually need a server process running 24/7? Most of the time, the answer is no. SQLite gets treated like a toy database, something for prototypes and side
I've been running Redis as a cache layer for years, and most setups I see out there are either over-engineered or barely doing anything useful. There's a sweet spot between caching everything and caching nothing, and it's smaller than you think. Here's