bbolt VS bolt

Based on this [GitHub document](https://github.com/etcd-io/bbolt) for BBoltDB, we can understand that Go Code be used to create a BBoltDB database on the system. The key-values added & operations done on them in that Go Code are stored in the BBoltDB database.

A Locker is a store on your file system (built on top of the amazing bbolt).

- bbolt for storage on disk. In order to get the smallest db file size possible make sure you insert the keys in order and set:

I'm wanting to store some wasm modules (as []byte) in BoltDB. Right now the modules are <1MB, but eventually, they could be 10-50MB in size. Is this going to reduce the performance of BoltDB all around, if the size of a value is this large? If it makes a difference, I'm using the Storm toolkit for querying.

bbolt - An embedded key/value database for Go.

For learning goroutines and channels, I usually recommend writing a program that reads from files and writes the data in a dummy database with something like https://github.com/etcd-io/bbolt. It's relatively simple and you're more likely to run into common manifestations of concurrency issues running disk operations.

If you would like to explore usage of channels, I highly recommend writing a program that reads from files and writes the data in a dummy database with something like https://github.com/etcd-io/bbolt.

No transactions, no consistency guarantees, no benchmarks, global locks in the storage implementation, a collection is copied in its entirety on every insertion to it...I realize it's not for the same use case as MySQL or MongoDB, but a more obvious comparison here is e.g. https://github.com/etcd-io/bbolt. So why should someone use this over bbolt?

use go-sqlite3 to work with sqlite3 is one choice.

https://github.com/etcd-io/bbolt is another pure go option.

cznic seems like an alternative to bbolt. nice to have some options.

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