Even for row-based data?

> DuckDB's columnar engine

That is workload specific. Title should be "Choose DuckDB rather than SQLite for Analytics" IMHO

great research there

TL;DR: SQLite was doing OLAP work it was never built for (and it was okay at it, I must add), and the perf. ceiling moves two orders of magnitude when you use something that's more fit for the purpose (DuckDB in this case).

TLDRTL;DR: If everything you do is column-store territory, use a column-store.

I ran this through an AI checker and it flagged half of it immediately. @dang, I know Substack just enabled Pangram integration, is there anyway you could get Y Combinator to spring for a Pangram subscription for the front page or something ?

Too bad Android doesn't have JDBC APIs. Getting the native binaries compiled on Android is the easy part, but there is no straightforward way to access it from Java. The Room APIs are tied to SQLite as well.

Great job on comparing apples to oranges. DuckDB is a columnar OLAP engine, SQLite is row-oriented OLTP. DuckDB should stomp SQLite in that particular use case.

Title, which is already synthetic, should be "Choose DuckDB rather than SQLite for Analytics Workloads".

AI slop. The content might be valuable but the framing makes it too painful to read.

Please, folks, write with your own voice -- especially if it's for your business blog. It's good for you as an author (practice makes perfect) and it's good for your readers (whom you want to influence).

How are these two DB engines even comparable other than at the edges? They handle two completely separate workload types: one is more a general-purpose DB engine and the other is specifically for columnar datasets, analytics and the like -- of course a hand-tuned DB engine is going to destroy SQLite on any reasonable benchmark: SQLite wouldn't be optimized for that hand-tuned use-case whereas something like DuckDB is.

Despite its obvious advantages, the biggest drawback of DuckDB is its concurrency model [1]. If a process opens a database in read-write mode, it acquires an exclusive lock on the file. This prevents even simple read operations from other processes as long as the writer remains open. Maybe there's a simple workaround I haven't come across, but I found it to be quite a productivity killer.

So yes, all these benchmarks are great, but it wasn't so fun working with DuckDB when I had to close duckdb cli, just so a query in another script could run.

[1]: https://duckdb.org/docs/current/connect/concurrency

This is a bait and switch article. Compare apples and oranges, "oh btw look at our product".

This is AI slop, but I really want to know more about their write patterns and how they were doing batches.