The simplicity of Gorilla is attractive but for better compression ratios without too much extra compute I'd instead recommend Sprintz: https://github.com/dblalock/sprintz.
The downside is that (a) Sprintz requires the data to be quantised to fixed point integers, usually fine if the data is coming out of a sensor of some sort and (b) the Huffman coding step of Sprintz requires dynamic memory allocation, whilst Gorilla is almost trivially implemented without it.
It doesn't really, except I suppose that both are called "databases". DuckDB is intended for OLAP, while Gorilla is specifically designed for time series data. You would never do something like "INSERT INTO users ..." with Gorilla.
The downside is that (a) Sprintz requires the data to be quantised to fixed point integers, usually fine if the data is coming out of a sensor of some sort and (b) the Huffman coding step of Sprintz requires dynamic memory allocation, whilst Gorilla is almost trivially implemented without it.
Also see Chimp, which proposes some small tweaks to Gorilla to improve its performance: https://dl.acm.org/doi/abs/10.14778/3551793.3551852