OLAP vs OLTP. Sure you could use one for the other, but they have ideal use cases. Updating a single record in SQLite is going to be more efficient than doing the same in DuckDB.

They seem similar at a glance but they’re quite different. You can think of SQLite as a transactional database while DuckDB is better used as an analytical database.

I can see applications having valid reasons to use both. You can use SQLite as the catalog in duck lake systems, for example. SQLite is your metadata record, DuckDB is your ingestion/scanning/aggregating/joining engine.

I wouldn’t see it as a replacement.

SQLite and DuckDB solve different problems and actually complement each other quite well. SQLite is excellent for transactional workloads (OLTP), while DuckDB shines for analytical workloads (OLAP), especially time-series data and aggregations.

We’ve been using both side-by-side in an open-source project for about two years: SQLite for configuration and transactional data, DuckDB for historical sensor data and analytics. So far, it’s been a very good combination.

You can even use DuckDB to query SQLite :^)

DuckDB kind of created this false comparison by their own early positioning, but I've tried to charitably interpret it as modeling the spirit and motivations of SQLite, not literally being "the SQLite for Analytics". Aside from both being in-process databases they are very different.