Every couple of hours, a cron job on a cheap LiteSpeed shared host wakes up, hits the YouTube Data API for eight regions — US, GB, DE, FR, IN, BR, AU, CA — and writes trending-video metadata into a single SQLite database. That is the entire ingestion pipeline behind TrendVidStream, a multi-region video streaming discovery site I run. PHP 8.4 renders the pages, SQLite FTS5 powers search, and deploys happen over plain FTP because that is what the hosting gives you. It works, it is boring, and it costs almost nothing.
What this setup does not handle gracefully is me, at 11pm, asking questions like: "Which videos trended in four or more regions this week, how fast did they climb, and is the music category quietly eating everything else?" Those are analytical questions — full scans, window functions, cross-snapshot joins. Running them against the production SQLite file means either hammering a shared-host CPU that is also serving traffic, or copying a multi-hundred-megabyte .db file to my laptop every time I get curious.
The fix that stuck: a nightly export of the hot tables to hive-partitioned Parquet, pulled down over the same FTP channel the deploys already use, and queried locally with DuckDB. The whole thing is about 120 lines of PHP and SQL, and it turned "I wonder if..." questions from a 20-minute chore into a 4-second query.
