SQLite VS bolt

If you are into alternative storage engines for SQLite, there is also an LSM (Log-Structured Merge-tree) extension in the main repository that is not announced nor documented but seems to work. It’s based on the SQLite 4 project.

https://github.com/sqlite/sqlite/tree/master/ext/lsm1

https://www.charlesleifer.com/blog/lsm-key-value-storage-in-...

The sqlite code base is really well done. Lots of documentation.

https://github.com/sqlite/sqlite

Especially the VM part: https://github.com/spandanb/learndb-py/blob/master/learndb/v...

Compare it with this: https://github.com/sqlite/sqlite/blob/master/src/vdbe.c

That's said, I'm curious how complete this LearnDB is. SQLite is hard to read not only it's old but also it covers a lot of SQL and following SQL spec makes hings complicated. SQLite has great test suite so it's nice if you run the suit against this implementation.

Correct, see the github mirror[1]. I don't know how well supported that feature is compared to main branch. If it was completely stable, then it would have already landed in the main stable branch. Clarity about the roadmap of that branch would be nice.

1. https://github.com/sqlite/sqlite/tree/begin-concurrent

Including comprehensive comments, documentation and tests in a codebase takes time and effort.

Failing to do so creates code that is very difficult to maintain or for someone new to the codebase to understand.

However, time and effort may not be what the organization wants to pay for, and individuals may view their own incomprehensible code as something like job security, as they can't be replaced by someone else easily.

As an example of complicated code that's still well-documented, the open-source sqlite code is a good example, about 1/4 of the B-tree file is comments, every time a variable is defined there's a short note explaining what it's used for, every function has a comment header that's comprehensive, such that someone new to the codebase could construct a map of how it all works fairly quickly. It's a good model for how to avoid the problem:

https://github.com/sqlite/sqlite/blob/master/src/btree.c

This crate started out as just a way for me to learn how boltdb works, while learning Rust at the same time. But somehow people started finding and using it and seem to like the simple API, so I figured I might as well share it in case someone else finds it useful too. If you want to know more about my motivations and the history of this crate, you can read the release notes on version 0.8.0!

Some example of embeddable database could be genji, badger and boltdb

Designing Data Intensive applications- specifically chapter 3 and 4 which deal with strategies and algorithms for storing and encoding data to be stored on disk and their pros and cons.

Once you read that, I'll suggest reading the source of a simple embedded key-value database, I wouldn't bother with RDBMs as they are complex beasts and contain way more than you need. BoltDB is a good project to read the source of https://github.com/boltdb/bolt, the whole thing is <10k lines of code and is a full blown production grade system with ACID semantics so packs a lot in those 10k and isn't just merely a toy.

Bolt db and Bolt db's author post to go with it.

https://github.com/boltdb/bolt is a ACID B+ tree key-value store

For a single server, SQLite, or boltdb[0]

I've never had to scale horizontally. I develop in Go and you can get very far along with just vertical scaling (aka beefier hardware).

Therefore I can't give concrete examples of a distributed db-as-a-library.

But all that you need is to extend the functions that fetch data to not just fetch from disk but from "peers" as well. For this to work you need servers (instances) to know about each other, and as you add more they also get added to their peers - sort of like a bittorrent network. I don't think it's difficult to do.

SQLite might not be suited for being distributed (although RQlite[1] claims to have done it).

Making a distributed data storage based on boltdb[0] is probably more feasible.

Whatever the case, there's no reason why a data storage engine can't be a library, even if it's distributed.

[0]: https://github.com/boltdb/bolt

[1]: https://github.com/rqlite/rqlite