I get where you're coming from. My books are also growing big right now, and indeed, they have become slower to process. Some projects in the community, such as Beanpost [1], are actually trying to solve the problem, as you said, by using an RMDB instead of plaintext.
But I still like text file format more for many reasons. The first would be the hot topic, which is about LLM friendliness. While I am still thinking about using AI to make the process even easier, with text-based accounting books, it's much easier to let AI process them and generate data for you.
Another reason is accessibility. Text-based accounting only requires an editor plus the CLI command line. Surely, you can build a friendly UI for SQLite-based books, but then so can text-based accounting books.
Yet another reason is, as you said, Git or VCS (Version control system) friendliness. With text-based, you can easily track all the changes from commit to commit for free and see what's changed. So, if I make a mistake in the book and I want to know when I made the mistake and how many years I need to go back and revise my reports, I can easily do that with Git.
Performance is a solvable technical challenge. We can break down the textbooks into smaller files and have a smart cache system to avoid parsing the same file repeatedly. Currently, I don't have the bandwidth to dig this rabbit hole, but I already have many ideas about how to improve performance when the file grows really big.