mongita

It's nice but it's no Mongita ;) https://github.com/scottrogowski/mongita In all seriousness, it seems like there's a lot of demand for embedded Mongo-like databases. Congrats on a successful Show HN post!

You're right. Fixed. SQLite is more-so the winner but Mongita appears to squeak ahead in id lookups https://github.com/scottrogowski/mongita/blob/master/assets/... (to be fair, it might be the thin translation layer I built). Regular MongoDB struggles a lot and I don't think I'm being unfair to it in any way afaik. Thank you for pointing that all out.

Oh thanks for the insight, that makes a lot of sense -- pretty sure mongita is one of the first projects I've seen even attempt this, and it makes sense to target the platform that fits your use case (and obviously everyone who uses PyMongo) the tightest. Your project looks very high quality -- benchmarks, tests, and comparisons are basically an indicator in my mind. Looking through the code you've also already left me (or someone else) space to try doing the SQLite as long as we implement it as an Engine[0] -- am I understanding that right? If I trace the code from database.py to engines/.py it looks like that. I really like the balance you've picked between pragmatism and space for expansion/modification. A couple questions: - How do you feel about type annotations in* the code (as opposed to just the comments, as far as I can see) - Py

It's a good question and to be accurate, depending on the benchmark, Mongita is about the same speed at SQLite to several-times slower. There is less happening algorithmically than you would think. Where the tricky slow bits do exist, they have largely fallen into the happy-path of fast data structures in the Python language/stdlib. I also use sortedcontainers for indexes which helped quite a bit (http://www.grantjenks.com/docs/sortedcontainers/). If you're curious, the benchmark code is in the repo: https://github.com/scottrogowski/mongita/blob/master/benchma...