[bambataa]

I had the exact same reaction.

I did a bit of reading about Datalog and I get that it’s useful in things like static analysis where you get the fixed point analysis for free, but apart from that I am not really sure why I’d use it.

[maweki]

The main reasons I'd say are the very intuitive JOINs and queries. Like you give some partial relation and you get every "fit". So as long as you mostly do equalities in JOIN and WHERE, the queries will be very intuitive and obvious to the layperson.

If you work with VIEWs or CTEs a lot, then Datalog is your friend, as every derived relationship is just a VIEW. If you like to encapsulate and reuse queries, then Datalog is ideal. We had plenty discussions on HN about SQL code reuse. Not an issue in Datalog.

And lastly, there are many ways to compile Datalog programs to "executables" that take maybe a few CSV-files as input and give you the results. I'm not saying that this would be always faster than loading the CSVs into SQLite and running SQL against the data, but a lot of work has been done on Datalog query optimization and compilers can emit very efficient code.

[samuell]

> If you like to encapsulate and reuse queries

This is what I always thought was the main benefit.

You are able to much easier raise your level of abstraction, by building up a vocabulary of definitions, and model your further queries (or definitions) using them.