That's not accurate: SQLite works great with data that's too big to fit in memory provided you create indexes and write queries that can take advantage of them - just like any other relational database (MySQL/PostgreSQL etc).
I guess it depends on what you’re trying to do. Creating those indices is going to require a scan through the whole data set, and you’re going to need to run a fair number of queries to amortize that. And if I’m going to be querying this data over and over again, that raises the question of why it wasn’t in a relational database to begin with.
In my personal experience I’m usually digging through structured logs to answer one or two questions, after which point I won’t need the exact same data set to be indexed the exact same way again. That’s often more easily done by converting the data to TSV and using awk and other command line tools, which is typically quicker and more parallelizable than loading the whole works into SQLite and doing the work there.
