Perhaps you already know this, but as a data store Prolog code is actually surprisingly convenient sometimes, similar to how you might create a throwaway SQLite

Perhaps you already know this, but as a data store Prolog code is actually surprisingly convenient sometimes, similar to how you might create a throwaway SQLite3 or DuckDB for a one-off analysis or recurring batched jobs. It's trivial to convert stuff like web server access logs into Prolog facts by either hacking the logging module or running the log files through a bit of sed, and then you can formalise some patterns as rules and do rather nifty querying. A hundred megabytes of RAM can hold a lot of log data as Prolog facts. E.g. '2024-11-16 12:45:27 127.0.0.1 "GET /something" "Whatever User-Agent" "user_id_123"' could be trivially transformed into 'logrow("2024-11-16", "12:45:27", "127.0.0.1", "GET", "/something", "Whatever User-Agent", "user_id_123").', especially if you're acquainted with DCG:s. Then you could, for example, write a rule that defines a relation between rows where a user-agent and IP does GET /log_out and shortly after has activity with another user ID, and query out people that could be suspected to use several accounts.